Pipeline run
d9fb549b-eb8e-484a-ac31-a35f6e78577e
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Backend Engineer
slug: backend-engineer · id: 14 · source: db
The role requires expertise in multiple backend technologies indicated by the primary skills.
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
ackend Engineer — Job Description Job Title: Backend Engineer Experience: 2–5 Years Location: Remote / Hybrid / Onsite About the Role We are looking for a Backend Engineer to build scalable, secure, and high-performance backend systems. You will work closely with frontend developers, product managers, and DevOps teams to design APIs, manage databases, and improve system reliability. Key Responsibilities Design and develop RESTful APIs and backend services Build scalable microservices and server-side applications Optimize application performance and database queries Implement authentication, authorization, and security best practices Integrate third-party APIs and cloud services Write clean, maintainable, and testable code Collaborate with frontend and DevOps teams for deployment and integration Monitor applications, debug issues, and improve system stability Participate in code reviews and technical discussions Required Skills Strong proficiency in Node.js / Java / Python / Go Experience with Express.js, Spring Boot, FastAPI, or similar frameworks Good understanding of REST APIs and microservices architecture Experience with databases such as PostgreSQL, MySQL, or MongoDB Knowledge of Redis, Kafka, or RabbitMQ is a plus Familiarity with Docker and Kubernetes Understanding of Git and CI/CD pipelines Knowledge of AWS, Azure, or GCP cloud platforms Strong problem-solving and debugging skills Preferred Qualifications Experience with scalable distributed systems Understanding of caching and performance optimization Familiarity with monitoring tools like Prometheus or Grafana Exposure to Agile/Scrum methodologies Nice to Have Experience with GraphQL Knowledge of event-driven architecture Open-source contributions or personal backend projects
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- DStreams (VERSION)
- Spark 2.x (VERSION)
- Spark 3.x (VERSION)
- Spark Streaming (VERSION)
- Spark Structured Streaming (VERSION)
- Structured Streaming (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Stream Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2013
- Confidence
- 0.90
- Version strategy
- SEPARATE_ENTITY
- Version tag
- Structured Streaming (Spark 2.0+)
Maturity reasoning: JD volume is far lower than Structured Streaming; most Spark streaming roles now specify Structured Streaming or Kafka/Flink, and Spark docs position Spark Streaming as the older API.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 67
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Integration and Data Fetching Catalog dimension db id 9
Library dimension (catalog)
Roles linked in library: Frontend Engineer, Full Stack Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- hooks composition (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Hooks Composition
- Confidence
- 0.92
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: React job postings commonly require hooks and custom hook composition; the pattern is standard in modern React codebases and docs, with broad ecosystem adoption rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- RUNTIME
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 271
- Sub-category id
- 2120
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages for Backend Systems Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- sqlmap (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Sql Injection Testing Tool
- Vendor
- sqlmap project
- License
- gpl_v2
- Year introduced
- 2006
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: sqlmap appears in pentest/security JDs far less than mainstream dev tools; GitHub shows steady but specialized use, and it’s a focused SQL injection testing utility rather than a general-purpose platform.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 54
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages for AI Workflows Catalog dimension db id 261
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Programming Languages for Backend Systems Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Backend Engineer
-
Programming Languages for Data Work Catalog dimension db id 67
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 113
Library dimension (catalog)
Roles linked in library: Machine Learning Engineer
-
Programming Languages for Test Automation Catalog dimension db id 193
Library dimension (catalog)
Roles linked in library: Automation Tester
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Cobalt Strike (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Adversary Simulation Tool
- Vendor
- Fortra
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Appears in a limited set of red-team/pentest JDs and security vendor training, but far below mainstream devops tools; market signal is specialized adversary-simulation usage rather than broad hiring demand.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 54
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Analytical Programming Languages Catalog dimension db id 82
Library dimension (catalog)
Roles linked in library: Data Analyst, Data Scientist
-
Automation Scripting and CLI Catalog dimension db id 48
Library dimension (catalog)
Roles linked in library: Azure Cloud Engineer, Cloud Engineer
-
Automation and Scripting for Operations Catalog dimension db id 361
Library dimension (catalog)
Roles linked in library: Virtualization Engineer
-
Network Automation and Scripting Catalog dimension db id 285
Library dimension (catalog)
Roles linked in library: Network Engineer
-
Programming Languages for AI Workflows Catalog dimension db id 261
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Programming Languages for Backend Systems Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Backend Engineer
-
Programming Languages for Data Work Catalog dimension db id 67
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 113
Library dimension (catalog)
Roles linked in library: Machine Learning Engineer
-
Programming Languages for Security Work Catalog dimension db id 328
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
-
Programming Languages for Test Automation Catalog dimension db id 193
Library dimension (catalog)
Roles linked in library: Automation Tester
-
Security Automation and Scripting Catalog dimension db id 258
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Analytical Programming Languages
analytical-programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Automation Scripting and CLI
automation-scripting-and-cli
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Automation and Scripting for Operations
automation-and-scripting-for-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Network Automation and Scripting
network-automation-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Security Work
programming-languages-for-security-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Security Automation and Scripting
security-automation-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- field-level errors (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Form Error Handling Concept
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common form UX pattern in web/mobile JDs and design-system docs; widely supported by libraries like React Hook Form, Formik, and Angular forms for per-field validation feedback.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 54
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages for Backend Systems Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Backend Engineer
-
Programming Languages for ML Systems Catalog dimension db id 113
Library dimension (catalog)
Roles linked in library: Machine Learning Engineer
-
Programming Languages for Security Work Catalog dimension db id 328
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Security Work
programming-languages-for-security-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- CDK (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Component Development Kit
- Vendor
- Amazon Web Services
- License
- apache_2
- Year introduced
- 2019
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS CDK appears in many cloud/DevOps job descriptions and is a standard IaC option alongside Terraform/CloudFormation, with strong GitHub activity and AWS vendor support.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 4
- Sub-category id
- 52
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- pagination (CANONICAL) primary
- Pagination (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Api Pagination
- Confidence
- 0.70
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common API design requirement in job descriptions for REST/GraphQL backends; widely implemented via page/limit or cursor patterns across major platforms and SDKs.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 4
- Sub-category id
- 708
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Inference Service Frameworks Catalog dimension db id 114
Library dimension (catalog)
Roles linked in library: Machine Learning Engineer
-
Web Service Frameworks Catalog dimension db id 141
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Inference Service Frameworks
inference-service-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Service Frameworks
web-service-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- GraphQL clients (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Library
- Sub-category
- Graphql Client Library
- Vendor
- Apollo GraphQL
- License
- mit
- Year introduced
- 2015
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: GraphQL clients are widely listed in frontend/backend JDs alongside Apollo/Relay, and major vendors maintain active docs and tooling; market demand is broad rather than niche.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 4
- Sub-category id
- 52
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Inference Service Frameworks Catalog dimension db id 114
Library dimension (catalog)
Roles linked in library: Machine Learning Engineer
-
Web Service Frameworks Catalog dimension db id 141
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Inference Service Frameworks
inference-service-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Service Frameworks
web-service-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — from this run (catalog unavailable)
- Microservices (CANONICAL) primary
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 663
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Service Architecture and Integration Catalog dimension db id 148
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Service Architecture and Integration
service-architecture-and-integration
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- PrimeNG (CANONICAL) primary
- PrimeNG 17 (VERSION)
- primeNG17 (VERSION)
- primeng 17.x (VERSION)
- primeng v17 (VERSION)
- primeng17 (VERSION)
- primeng@17 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Ui Component Framework
- Vendor
- PrimeFaces
- License
- mit
- Year introduced
- 2015
- Confidence
- 0.92
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 17
Maturity reasoning: PrimeNG appears in some Angular UI job postings and has active GitHub usage, but JD volume is far below React/Angular Material and it’s usually a library preference, not a core requirement.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 627
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- NG-ZORRO (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Ui Component Framework
- Vendor
- NG-ZORRO
- License
- mit
- Year introduced
- 2017
- Confidence
- 0.92
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NG-ZORRO appears in a limited number of Angular UI job postings and is mainly used in Ant Design-based enterprise apps; market demand is far below mainstream Angular Material or React UI libraries.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 627
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Data Access and Query Optimization Catalog dimension db id 74
Library dimension (catalog)
Roles linked in library: Data Engineer
-
MySQL Operational Monitoring, Logging, and Diagnostics Catalog dimension db id 166
Library dimension (catalog)
Roles linked in library: MySQL DBA
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Data Access and Query Optimization
data-access-and-query-optimization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
MySQL Operational Monitoring, Logging, and Diagnostics
mysql-operational-monitoring-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- STIX/TAXII (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Standard
- Sub-category
- Threat Intelligence Exchange Standard
- Vendor
- OASIS
- License
- other_open
- Year introduced
- 2012
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: STIX/TAXII appears in threat-intel and SOC job postings, but JD volume is far below mainstream standards; it’s mainly used in specialized CTI platforms and vendor integrations rather than general software roles.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 360
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL and Cache Stores Catalog dimension db id 145
Library dimension (catalog)
Roles linked in library: Backend Engineer
-
NoSQL and Data Lake Storage Catalog dimension db id 73
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL and Cache Stores
nosql-and-cache-stores
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
NoSQL and Data Lake Storage
nosql-and-data-lake-storage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- idempotent configuration (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Configuration Concept
- Confidence
- 0.86
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common DevOps/SRE requirement in JDs for Ansible, Terraform, and Kubernetes: "idempotent" appears frequently in automation and IaC roles, reflecting broad market adoption.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 701
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL and Cache Stores Catalog dimension db id 145
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL and Cache Stores
nosql-and-cache-stores
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- image scanning (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Security Scanning Tool
- Vendor
- Aqua Security
- License
- apache_2
- Year introduced
- 2015
- Confidence
- 0.80
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Image scanning is widely listed in DevSecOps JDs and CI/CD security stacks; vendors like Trivy, Snyk, and Prisma Cloud have made container/image scanning a standard market requirement.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 700
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Messaging and Event Streaming Catalog dimension db id 146
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — from this run (catalog unavailable)
- RabbitMQ (CANONICAL) primary
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 743
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Messaging and Event Streaming Catalog dimension db id 146
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Metabase (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Bi Analytics Tool
- Vendor
- Metabase, Inc.
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Metabase appears in many BI/analytics job postings and is growing in GitHub usage, but it is still far less universal than Tableau/Power BI in enterprise JDs.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 170
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Containerization and Image Delivery Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Model Serving Deployment and Runtime Packaging Catalog dimension db id 52
Library dimension (catalog)
Roles linked in library: MLOps Engineer, Machine Learning Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Containerization and Image Delivery
containerization-and-image-delivery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Model Serving Deployment and Runtime Packaging
model-serving-deployment-and-runtime-packaging
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Column-level security (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Access Control Concept
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Appears in cloud/data platform JDs and vendor docs for Snowflake, BigQuery, and PostgreSQL RLS/column masking, but is not yet a universal hiring staple like core IAM or RBAC.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 1524
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Orchestration Platforms Catalog dimension db id 25
Library dimension (catalog)
Roles linked in library: Cloud Engineer, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Orchestration Platforms
orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — from this run (catalog unavailable)
- Git (CANONICAL)
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 2101
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — from this run (catalog unavailable)
- CI/CD (CANONICAL)
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 2102
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Compaction (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Storage Maintenance Concept
- Confidence
- 0.74
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Compaction is a standard storage-maintenance concept in widely used systems like LSM databases and Kafka; it appears in many JDs for Cassandra, RocksDB, and Kafka ops roles, indicating broad market demand.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 161
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platform Operations Catalog dimension db id 26
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Cloud Security Platforms Catalog dimension db id 332
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platform Operations
cloud-platform-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Compute right-sizing (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Capacity Planning Methodology
- Confidence
- 0.78
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common cloud/capacity-planning practice; widely referenced in AWS/Azure/GCP cost-optimization docs and frequently appears in FinOps and SRE job descriptions focused on reducing overprovisioning.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 161
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platform Operations Catalog dimension db id 26
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Cloud Security Platforms Catalog dimension db id 332
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platform Operations
cloud-platform-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- ASGI (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Protocol
- Sub-category
- Web Application Protocol
- Vendor
- Django Software Foundation
- License
- bsd
- Year introduced
- 2016
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: ASGI appears in many Python web JDs for async frameworks like FastAPI/Starlette, but WSGI remains the broader default in legacy stacks; market signal shows growing adoption rather than universal demand.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 161
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Security Platforms Catalog dimension db id 332
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Replay processing (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Data Reprocessing Methodology
- Confidence
- 0.77
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Replay processing appears in specialized data/streaming and event-sourcing JDs, but far less often than core ETL or batch processing; market demand is concentrated in a narrow set of platforms and teams.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 729
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Observability and Alerting Catalog dimension db id 27
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Observability and Diagnostics Catalog dimension db id 151
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Observability and Alerting
observability-and-alerting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Diagnostics
observability-and-diagnostics
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Recovery runbooks (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Operational Runbook Methodology
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common SRE/ops requirement: many job descriptions for DevOps/SRE/Platform roles explicitly ask for incident response and recovery runbooks, and major vendors like AWS/Azure document runbooks as standard operational practice.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 331
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Observability and Alerting Catalog dimension db id 27
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Observability and Diagnostics Catalog dimension db id 151
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Observability and Alerting
observability-and-alerting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Diagnostics
observability-and-diagnostics
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — from this run (catalog unavailable)
- Agile (CANONICAL)
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 2124
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Project Delivery and Coordination Catalog dimension db id 366
Library dimension (catalog)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Project Delivery and Coordination
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — from this run (catalog unavailable)
- Scrum (CANONICAL)
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 2125
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- structured logging (CANONICAL) primary
- Structured logging (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Structured Logging
- Confidence
- 0.91
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly required in JDs for observability/SRE roles and supported by major stacks (e.g., JSON logs in ELK, Datadog, OpenTelemetry); market demand is broad rather than niche.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 651
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Integration and Data Fetching Catalog dimension db id 9
Library dimension (catalog)
Roles linked in library: Frontend Engineer, Full Stack Developer
-
API Integration and Serialization Catalog dimension db id 128
Library dimension (catalog)
Roles linked in library: iOS Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
API Integration and Serialization
api-integration-and-serialization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- pre-production signoff (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- SoftSkill
- Sub-category
- Approval Coordination
- Confidence
- 0.78
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common release-gate requirement in JDs for QA/release managers and DevOps; often listed as UAT/production approval or go-live signoff in enterprise hiring pipelines.
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 911
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Service Integration Patterns Catalog dimension db id 188
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Service Integration Patterns
cloud-service-integration-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| REST | in_db |
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Node.js | in_db |
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Java | in_db |
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Java | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Analytical Programming Languages
analytical-programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Automation Scripting and CLI
automation-scripting-and-cli
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Automation and Scripting for Operations
automation-and-scripting-for-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Network Automation and Scripting
network-automation-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Security Work
programming-languages-for-security-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Security Automation and Scripting
security-automation-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Go | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Programming Languages for Security Work
programming-languages-for-security-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Express.js | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Spring Boot | in_db |
Inference Service Frameworks
inference-service-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Spring Boot | in_db |
Web Service Frameworks
web-service-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| FastAPI | in_db |
Inference Service Frameworks
inference-service-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| FastAPI | in_db |
Web Service Frameworks
web-service-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Microservices | in_db |
Service Architecture and Integration
service-architecture-and-integration
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| PostgreSQL | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Data Access and Query Optimization
data-access-and-query-optimization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
MySQL Operational Monitoring, Logging, and Diagnostics
mysql-operational-monitoring-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MongoDB | in_db |
NoSQL and Cache Stores
nosql-and-cache-stores
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| MongoDB | in_db |
NoSQL and Data Lake Storage
nosql-and-data-lake-storage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Redis | in_db |
NoSQL and Cache Stores
nosql-and-cache-stores
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Kafka | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| RabbitMQ | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Docker | in_db |
Containerization and Image Delivery
containerization-and-image-delivery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Model Serving Deployment and Runtime Packaging
model-serving-deployment-and-runtime-packaging
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Orchestration Platforms
orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Git | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Platform Operations
cloud-platform-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platform Operations
cloud-platform-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GCP | in_db |
Cloud Security Platforms
cloud-security-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Alerting
observability-and-alerting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Diagnostics
observability-and-diagnostics
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Grafana | in_db |
Observability and Alerting
observability-and-alerting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Grafana | in_db |
Observability and Diagnostics
observability-and-diagnostics
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Agile | in_db |
Project Delivery and Coordination
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Scrum | in_db |
Version Control Systems
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GraphQL | in_db |
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GraphQL | in_db |
API Integration and Serialization
api-integration-and-serialization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Event-Driven Architecture | in_db |
Cloud Service Integration Patterns
cloud-service-integration-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Enterprise Software",
"B2B Software"
],
"domain": "Software \u0026 SaaS Products"
},
"secondary": null
},
"education": [],
"experience": {
"max": 5,
"min": 2,
"raw": "2\u20135 Years"
},
"job_locations": [
{
"aliases": [],
"city": null,
"country": null,
"state": null,
"work_mode": "remote"
},
{
"aliases": [],
"city": null,
"country": null,
"state": null,
"work_mode": "hybrid"
},
{
"aliases": [],
"city": null,
"country": null,
"state": null,
"work_mode": "onsite"
}
],
"role": "Backend Engineer",
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 9,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Design and develop RESTful APIs",
"last_5_words": "discussions"
},
"text": "Design and develop RESTful APIs and backend services\nBuild scalable microservices and server-side applications\nOptimize application performance and database queries\nImplement authentication, authorization, and security best practices\nIntegrate third-party APIs and cloud services\nWrite clean, maintainable, and testable code\nCollaborate with frontend and DevOps teams for deployment and integration\nMonitor applications, debug issues, and improve system stability\nParticipate in code reviews and technical discussions",
"word_count": 86
},
{
"bullet_count": 9,
"heading": "Required Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Strong proficiency in Node.js",
"last_5_words": "debugging skills"
},
"text": "Strong proficiency in Node.js / Java / Python / Go\nExperience with Express.js, Spring Boot, FastAPI, or similar frameworks\nGood understanding of REST APIs and microservices architecture\nExperience with databases such as PostgreSQL, MySQL, or MongoDB\nKnowledge of Redis, Kafka, or RabbitMQ is a plus\nFamiliarity with Docker and Kubernetes\nUnderstanding of Git and CI/CD pipelines\nKnowledge of AWS, Azure, or GCP cloud platforms\nStrong problem-solving and debugging skills",
"word_count": 94
},
{
"bullet_count": 4,
"heading": "Preferred Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience with scalable distributed systems",
"last_5_words": "methodologies"
},
"text": "Experience with scalable distributed systems\nUnderstanding of caching and performance optimization\nFamiliarity with monitoring tools like Prometheus or Grafana\nExposure to Agile/Scrum methodologies",
"word_count": 36
},
{
"bullet_count": 3,
"heading": "Nice to Have",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience with GraphQL",
"last_5_words": "projects"
},
"text": "Experience with GraphQL\nKnowledge of event-driven architecture\nOpen-source contributions or personal backend projects",
"word_count": 20
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
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{
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{
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"last_5_words": "discussions"
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"source_marker": {
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"last_5_words": "debugging skills"
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API 2 — extract-details
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},
{
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},
{
"dimension": {
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},
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},
{
"dimension": {
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"slug": "nosql-and-data-lake-storage",
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},
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"roles_from_db": [
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]
},
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"dimension": {
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"slug": "nosql-and-cache-stores",
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},
"input_skill": "Redis",
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"slug": "d_init_01",
"source": "db"
},
"input_skill": "Agile",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Agile",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Scrum",
"alias_type": "CANONICAL",
"id": 3402,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 7,
"display_name": "Scrum",
"id": 2605,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "scrum",
"sub_category_id": 2125,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Scrum",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Scrum",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "GraphQL",
"alias_type": "CANONICAL",
"id": 175,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "GraphQL",
"id": 50,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "graphql",
"sub_category_id": 651,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Data Fetching",
"id": 9,
"rationale": "Connecting frontend applications to backend services and third-party endpoints. This covers request orchestration, error handling, pagination, and shaping remote data for UI consumption.",
"slug": "api-integration-and-data-fetching",
"source": "db"
},
"input_skill": "GraphQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Frontend Engineer",
"id": 3,
"rationale": null,
"role_archetype": "Frontend Engineers design and build the user-facing parts of applications, translating product and design requirements into interactive experiences. They focus on how the application looks, behaves, and responds in the browser, ensuring usability, accessibility, and consistency across the interface.",
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Full Stack Developer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Serialization",
"id": 128,
"rationale": "Client-side integration with backend services, including request handling, response parsing, and contract alignment. This cluster is coherent because iOS features frequently depend on stable data exchange with server APIs.",
"slug": "api-integration-and-serialization",
"source": "db"
},
"input_skill": "GraphQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "iOS Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
]
}
],
"input_skill": "GraphQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Event-driven architecture",
"alias_type": "CANONICAL",
"id": 1630,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 1,
"display_name": "Event-driven architecture",
"id": 1156,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PATTERN",
"slug": "event-driven-architecture",
"sub_category_id": 911,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Service Integration Patterns",
"id": 188,
"rationale": "Covers how cloud services and workloads connect through APIs, events, shared services, and integration boundaries. This cluster is coherent because architects must define interaction patterns that preserve decoupling, security, and operability.",
"slug": "cloud-service-integration-patterns",
"source": "db"
},
"input_skill": "Event-Driven Architecture",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
}
],
"input_skill": "Event-Driven Architecture",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": []
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Backend Engineer",
"id": 14,
"rationale": "The role requires expertise in multiple backend technologies indicated by the primary skills.",
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "REST",
"tag": "in_db"
},
{
"skill": "Node.js",
"tag": "in_db"
},
{
"skill": "Java",
"tag": "in_db"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Go",
"tag": "in_db"
},
{
"skill": "Express.js",
"tag": "in_db"
},
{
"skill": "Spring Boot",
"tag": "in_db"
},
{
"skill": "FastAPI",
"tag": "in_db"
},
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "PostgreSQL",
"tag": "in_db"
},
{
"skill": "MySQL",
"tag": "in_db"
},
{
"skill": "MongoDB",
"tag": "in_db"
},
{
"skill": "Redis",
"tag": "in_db"
},
{
"skill": "Kafka",
"tag": "in_db"
},
{
"skill": "RabbitMQ",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "Git",
"tag": "in_db"
},
{
"skill": "CI/CD",
"tag": "in_db"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "GCP",
"tag": "in_db"
},
{
"skill": "Prometheus",
"tag": "in_db"
},
{
"skill": "Grafana",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
},
{
"skill": "Scrum",
"tag": "in_db"
},
{
"skill": "GraphQL",
"tag": "in_db"
},
{
"skill": "Event-Driven Architecture",
"tag": "in_db"
}
],
"persistence": {
"items": [
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Data Fetching",
"id": 9,
"rationale": "Connecting frontend applications to backend services and third-party endpoints. This covers request orchestration, error handling, pagination, and shaping remote data for UI consumption.",
"slug": "api-integration-and-data-fetching",
"source": "db"
},
"dimension_id": 9,
"input_skill": "REST",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Frontend Engineer",
"id": 3,
"rationale": null,
"role_archetype": "Frontend Engineers design and build the user-facing parts of applications, translating product and design requirements into interactive experiences. They focus on how the application looks, behaves, and responds in the browser, ensuring usability, accessibility, and consistency across the interface.",
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Full Stack Developer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 121,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"dimension_id": 140,
"input_skill": "Node.js",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2599,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for AI Workflows",
"id": 261,
"rationale": "Languages used to implement AI feature logic, orchestration, and response handling inside product code. This is the core coding surface for turning prompts and model calls into reliable application behavior.",
"slug": "programming-languages-for-ai-workflows",
"source": "db"
},
"dimension_id": 261,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"dimension_id": 140,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 67,
"rationale": "Languages used to implement data pipelines, transformations, and operational utilities. This is the code layer for expressing extraction, parsing, validation, and orchestration logic in data engineering workflows.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 67,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 113,
"rationale": "Languages used to implement model integration code, inference services, and feature-processing logic. This is the core coding surface for turning trained models into product-facing software components.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 113,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Test Automation",
"id": 193,
"rationale": "Languages used to implement automated checks, helper utilities, and test harness code. This is the core coding surface for turning test ideas into maintainable automation.",
"slug": "programming-languages-for-test-automation",
"source": "db"
},
"dimension_id": 193,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Automation Tester",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "automation-tester",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Analytical Programming Languages",
"id": 82,
"rationale": "Languages used to clean, transform, analyze, and prototype models in notebooks and scripts. This is the core coding surface for expressing statistical logic and data manipulation in a reproducible way.",
"slug": "analytical-programming-languages",
"source": "db"
},
"dimension_id": 82,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Analyst",
"id": 20,
"rationale": null,
"role_archetype": null,
"slug": "data-analyst",
"source": "db"
},
{
"display_name": "Data Scientist",
"id": 7,
"rationale": null,
"role_archetype": null,
"slug": "data-scientist",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Automation Scripting and CLI",
"id": 48,
"rationale": "Uses scripts and command-line tooling to execute repeatable Azure operations and reduce manual work. This is a practical cluster because the role frequently automates provisioning, checks, and remediation tasks.",
"slug": "automation-scripting-and-cli",
"source": "db"
},
"dimension_id": 48,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Azure Cloud Engineer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "azure-cloud-engineer",
"source": "db"
},
{
"display_name": "Cloud Engineer",
"id": 18,
"rationale": null,
"role_archetype": null,
"slug": "cloud-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Automation and Scripting for Operations",
"id": 361,
"rationale": "Scripts and lightweight automation used to execute repetitive virtualization tasks and enforce operational consistency. This is the practical glue that reduces manual host and VM administration.",
"slug": "automation-and-scripting-for-operations",
"source": "db"
},
"dimension_id": 361,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Virtualization Engineer",
"id": 26,
"rationale": null,
"role_archetype": null,
"slug": "virtualization-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Network Automation and Scripting",
"id": 285,
"rationale": "Covers scripts and automation used to configure, validate, and audit network devices and services. This cluster is coherent because repeatable network operations increasingly depend on programmatic changes and checks.",
"slug": "network-automation-and-scripting",
"source": "db"
},
"dimension_id": 285,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Network Engineer",
"id": 21,
"rationale": null,
"role_archetype": null,
"slug": "network-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for AI Workflows",
"id": 261,
"rationale": "Languages used to implement AI feature logic, orchestration, and response handling inside product code. This is the core coding surface for turning prompts and model calls into reliable application behavior.",
"slug": "programming-languages-for-ai-workflows",
"source": "db"
},
"dimension_id": 261,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"dimension_id": 140,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 67,
"rationale": "Languages used to implement data pipelines, transformations, and operational utilities. This is the code layer for expressing extraction, parsing, validation, and orchestration logic in data engineering workflows.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 67,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 113,
"rationale": "Languages used to implement model integration code, inference services, and feature-processing logic. This is the core coding surface for turning trained models into product-facing software components.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 113,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
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"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Security Work",
"id": 328,
"rationale": "Languages used to automate security tasks, write detection logic, and build analysis or remediation tooling. This is the core coding surface for a cybersecurity engineer across scripts, queries, and small utilities.",
"slug": "programming-languages-for-security-work",
"source": "db"
},
"dimension_id": 328,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
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"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Test Automation",
"id": 193,
"rationale": "Languages used to implement automated checks, helper utilities, and test harness code. This is the core coding surface for turning test ideas into maintainable automation.",
"slug": "programming-languages-for-test-automation",
"source": "db"
},
"dimension_id": 193,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Automation Tester",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "automation-tester",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Security Automation and Scripting",
"id": 258,
"rationale": "Automating repeatable security checks, enrichment, and remediation workflows. This cluster is coherent because the role often needs lightweight automation to scale analysis and response.",
"slug": "security-automation-and-scripting",
"source": "db"
},
"dimension_id": 258,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 393,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"dimension_id": 140,
"input_skill": "Go",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 679,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 113,
"rationale": "Languages used to implement model integration code, inference services, and feature-processing logic. This is the core coding surface for turning trained models into product-facing software components.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 113,
"input_skill": "Go",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 679,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Security Work",
"id": 328,
"rationale": "Languages used to automate security tasks, write detection logic, and build analysis or remediation tooling. This is the core coding surface for a cybersecurity engineer across scripts, queries, and small utilities.",
"slug": "programming-languages-for-security-work",
"source": "db"
},
"dimension_id": 328,
"input_skill": "Go",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
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"skill_id": 679,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "Express.js",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2668,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Inference Service Frameworks",
"id": 114,
"rationale": "Web and service frameworks used to expose model predictions through APIs and application endpoints. This cluster is coherent because MLEs often implement the runtime surface where requests enter and predictions leave the system.",
"slug": "inference-service-frameworks",
"source": "db"
},
"dimension_id": 114,
"input_skill": "Spring Boot",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 684,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Service Frameworks",
"id": 141,
"rationale": "Server frameworks used to build HTTP APIs, route requests, validate inputs, and structure backend application code. This cluster is coherent because it defines how backend services expose behavior to clients and other services.",
"slug": "web-service-frameworks",
"source": "db"
},
"dimension_id": 141,
"input_skill": "Spring Boot",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 684,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Inference Service Frameworks",
"id": 114,
"rationale": "Web and service frameworks used to expose model predictions through APIs and application endpoints. This cluster is coherent because MLEs often implement the runtime surface where requests enter and predictions leave the system.",
"slug": "inference-service-frameworks",
"source": "db"
},
"dimension_id": 114,
"input_skill": "FastAPI",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 682,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Service Frameworks",
"id": 141,
"rationale": "Server frameworks used to build HTTP APIs, route requests, validate inputs, and structure backend application code. This cluster is coherent because it defines how backend services expose behavior to clients and other services.",
"slug": "web-service-frameworks",
"source": "db"
},
"dimension_id": 141,
"input_skill": "FastAPI",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 682,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Service Architecture and Integration",
"id": 148,
"rationale": "Patterns for structuring backend systems as services and coordinating calls across internal and external dependencies. This includes how services are decomposed, connected, and evolved safely.",
"slug": "service-architecture-and-integration",
"source": "db"
},
"dimension_id": 148,
"input_skill": "Microservices",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 864,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "PostgreSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2669,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Data Access and Query Optimization",
"id": 74,
"rationale": "Techniques for making analytical data fast and reliable to query. This includes partitioning, clustering, indexing choices, file layout, and access-path tuning for downstream consumers.",
"slug": "data-access-and-query-optimization",
"source": "db"
},
"dimension_id": 74,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2670,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "MySQL Operational Monitoring, Logging, and Diagnostics",
"id": 166,
"rationale": "Covers the DBA practice of monitoring MySQL production health and using MySQL-native logs and diagnostic views to detect, investigate, and explain incidents or performance anomalies. Includes routine health checks, alerting, replication and availability monitoring, resource and connection monitoring, and use of error logs, slow query logs, SHOW PROCESSLIST, performance_schema, status variables, and diagnostic queries to understand behavior and support recovery decisions.",
"slug": "mysql-operational-monitoring-logging-and-diagnostics",
"source": "db"
},
"dimension_id": 166,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "MySQL DBA",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "mysql-dba",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2670,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL and Cache Stores",
"id": 145,
"rationale": "Non-relational databases and in-memory stores used for low-latency access, flexible schemas, and specialized persistence patterns. This cluster is coherent because backend services often combine these stores with relational systems.",
"slug": "nosql-and-cache-stores",
"source": "db"
},
"dimension_id": 145,
"input_skill": "MongoDB",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 432,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL and Data Lake Storage",
"id": 73,
"rationale": "Non-relational stores and lake storage used for semi-structured, large-scale, or raw data retention. This cluster is coherent because many pipelines land and serve data outside classic relational warehouses.",
"slug": "nosql-and-data-lake-storage",
"source": "db"
},
"dimension_id": 73,
"input_skill": "MongoDB",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 432,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL and Cache Stores",
"id": 145,
"rationale": "Non-relational databases and in-memory stores used for low-latency access, flexible schemas, and specialized persistence patterns. This cluster is coherent because backend services often combine these stores with relational systems.",
"slug": "nosql-and-cache-stores",
"source": "db"
},
"dimension_id": 145,
"input_skill": "Redis",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 846,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 146,
"rationale": "Asynchronous communication patterns and systems for decoupled service interaction and background processing. This is a coherent backend cluster because many server-side workflows depend on queues, topics, and event streams.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 146,
"input_skill": "Kafka",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 852,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 146,
"rationale": "Asynchronous communication patterns and systems for decoupled service interaction and background processing. This is a coherent backend cluster because many server-side workflows depend on queues, topics, and event streams.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 146,
"input_skill": "RabbitMQ",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 853,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Containerization and Image Delivery",
"id": 24,
"rationale": "Builds, packages, and ships application and support workloads as container images. This cluster covers the artifact format and the mechanics of producing deployable images.",
"slug": "containerization-and-image-delivery",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 153,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Model Serving Deployment and Runtime Packaging",
"id": 52,
"rationale": "Operational deployment of trained models into online, batch, or streaming serving environments, including packaging models and model servers into containers or managed inference runtimes, coordinating rollout, and handing off to inference systems. Covers serving frameworks and platforms such as TensorFlow Serving, TorchServe, Triton Inference Server, BentoML, KServe, and Seldon Core, plus container/runtime concerns like Docker images, GPU-enabled containers, base image selection, container entrypoints, runtime dependencies, and image scanning for model services.",
"slug": "model-serving-deployment-and-runtime-packaging",
"source": "db"
},
"dimension_id": 52,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "MLOps Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "mlops-engineer",
"source": "db"
},
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 153,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Orchestration Platforms",
"id": 25,
"rationale": "Operates the platforms that schedule and run containerized workloads and related deployment primitives. This is separate from image delivery because it concerns runtime placement and service rollout behavior.",
"slug": "orchestration-platforms",
"source": "db"
},
"dimension_id": 25,
"input_skill": "Kubernetes",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Engineer",
"id": 18,
"rationale": null,
"role_archetype": null,
"slug": "cloud-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 158,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "Git",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2578,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "CI/CD",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2579,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"dimension_id": 26,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 163,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Platforms",
"id": 332,
"rationale": "Cloud-native security products used to assess posture, detect misconfigurations, and monitor workloads across AWS, Azure, and GCP. This is a distinct product family because the role often works across multiple CNAPP/CSPM/CWPP offerings and cloud-native detectors.",
"slug": "cloud-security-platforms",
"source": "db"
},
"dimension_id": 332,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 163,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"dimension_id": 26,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 164,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Platforms",
"id": 332,
"rationale": "Cloud-native security products used to assess posture, detect misconfigurations, and monitor workloads across AWS, Azure, and GCP. This is a distinct product family because the role often works across multiple CNAPP/CSPM/CWPP offerings and cloud-native detectors.",
"slug": "cloud-security-platforms",
"source": "db"
},
"dimension_id": 332,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 164,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Platforms",
"id": 332,
"rationale": "Cloud-native security products used to assess posture, detect misconfigurations, and monitor workloads across AWS, Azure, and GCP. This is a distinct product family because the role often works across multiple CNAPP/CSPM/CWPP offerings and cloud-native detectors.",
"slug": "cloud-security-platforms",
"source": "db"
},
"dimension_id": 332,
"input_skill": "GCP",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2304,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Alerting",
"id": 27,
"rationale": "Builds feedback loops for system health through metrics, logs, traces, dashboards, and alerts. This cluster is coherent because it turns runtime behavior into actionable operational signals.",
"slug": "observability-and-alerting",
"source": "db"
},
"dimension_id": 27,
"input_skill": "Prometheus",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 168,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Diagnostics",
"id": 151,
"rationale": "Logging, metrics, tracing, dashboards, and debugging practices used to understand backend behavior in production. This cluster is coherent because backend engineers must detect failures, performance issues, and unexpected behavior.",
"slug": "observability-and-diagnostics",
"source": "db"
},
"dimension_id": 151,
"input_skill": "Prometheus",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 168,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Alerting",
"id": 27,
"rationale": "Builds feedback loops for system health through metrics, logs, traces, dashboards, and alerts. This cluster is coherent because it turns runtime behavior into actionable operational signals.",
"slug": "observability-and-alerting",
"source": "db"
},
"dimension_id": 27,
"input_skill": "Grafana",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 169,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Diagnostics",
"id": 151,
"rationale": "Logging, metrics, tracing, dashboards, and debugging practices used to understand backend behavior in production. This cluster is coherent because backend engineers must detect failures, performance issues, and unexpected behavior.",
"slug": "observability-and-diagnostics",
"source": "db"
},
"dimension_id": 151,
"input_skill": "Grafana",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 169,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Project Delivery and Coordination",
"id": 366,
"rationale": "Coordination practices for organizing work, tracking progress, and aligning stakeholders across a delivery effort. Agile fits here when used as a team execution framework for managing scope, cadence, and collaboration.",
"slug": "d_init_02",
"source": "db"
},
"dimension_id": 366,
"input_skill": "Agile",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2604,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "Agile",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2604,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Version Control Systems",
"id": 365,
"rationale": "Tools and workflows for tracking source changes, branching, merging, and collaborating on code history. Git belongs here because it is the canonical distributed version control system used to manage revisions and coordinate team development.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 365,
"input_skill": "Scrum",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2605,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Data Fetching",
"id": 9,
"rationale": "Connecting frontend applications to backend services and third-party endpoints. This covers request orchestration, error handling, pagination, and shaping remote data for UI consumption.",
"slug": "api-integration-and-data-fetching",
"source": "db"
},
"dimension_id": 9,
"input_skill": "GraphQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Frontend Engineer",
"id": 3,
"rationale": null,
"role_archetype": "Frontend Engineers design and build the user-facing parts of applications, translating product and design requirements into interactive experiences. They focus on how the application looks, behaves, and responds in the browser, ensuring usability, accessibility, and consistency across the interface.",
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Full Stack Developer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 50,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
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"display_name": "API Integration and Serialization",
"id": 128,
"rationale": "Client-side integration with backend services, including request handling, response parsing, and contract alignment. This cluster is coherent because iOS features frequently depend on stable data exchange with server APIs.",
"slug": "api-integration-and-serialization",
"source": "db"
},
"dimension_id": 128,
"input_skill": "GraphQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "iOS Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 50,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 14,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Service Integration Patterns",
"id": 188,
"rationale": "Covers how cloud services and workloads connect through APIs, events, shared services, and integration boundaries. This cluster is coherent because architects must define interaction patterns that preserve decoupling, security, and operability.",
"slug": "cloud-service-integration-patterns",
"source": "db"
},
"dimension_id": 188,
"input_skill": "Event-Driven Architecture",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1156,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "d9fb549b-eb8e-484a-ac31-a35f6e78577e"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.