Pipeline run
466e3948-0a2d-4c89-ab8a-eb42e93eda0e
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
Full Stack Developer
slug: full-stack-developer · id: 2 · source: db
The primary skills involve both front-end (ReactJS, JavaScript, TypeScript) and back-end (NodeJS, MongoDB) technologies.
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
About the job About CoverForce At CoverForce, we're on a mission to transform the insurance industry by making it faster and easier for businesses to get the coverage they need. Now is the perfect time to join our team and help shape the future of insurtech. Thousands of insurance agents and corporate customers depend on our tools to simplify quoting, comparing, and buying insurance policies. We partner with top insurers like Travelers, Liberty Mutual, and Chubb to streamline underwriting and sales, cutting the time spent on a single insurance policy by 75%. Our Innovative Solutions Include Quote and Bind Platform: Trusted by several of the Top 100 insurance distributors in the US, our platform lets agents generate and purchase business insurance quotes with a single click, saving time and eliminating repetitive paperwork. Carriers also use it to digitally empower their appointed agencies. Embedded Commercial Product: This allows partners like Walmart, Gusto, and Uber to offer business insurance directly through their platforms using our API. It also integrates with other Agency Management Systems to enhance their quote and binding capabilities. We're positioned to be the central API for insurance distribution, much like how Plaid has transformed banking. Whether through our user-friendly web platform or our powerful API, CoverForce is here to make insurance purchasing easy, digital and efficient. Join us and be part of a team that's dedicated to innovation and excellence. We are headquartered in New York City and have our engineering team based in India. The Opportunity As an engineer at CoverForce, you will work on designing and implementing the core infrastructure of the API platform. You will work on Carrier Integrations, partner integrations, developing the CoverForce engine, and other core features of the product. As we build out our Public API, you will be involved in discussions about the structure, models, synchronicity, and other key decisions of a complex Public facing API. This role is a perfect fit for an engineer who thrives in fast-paced environments looking to build a product from the ground up. You will have the opportunity to take ownership and wear many hats as you develop the product. As an early engineer, you'll impact product development, system architecture, engineering culture, and more. You will work across the stack building out our centralized API and the front-end portal. We use ReactJS, NodeJS, MongoDB, Docker, and Javascript/Typescript on AWS. Our product was inspired by talking with 100s of agents and identifying the critical pain points in the quote, bind, and payment process. We see our solution scaling to independent agencies, agency management systems, and corporate customers. Tasks Will Include Integrating with Insurance carriers Researching the API of an insurance carrier. Designing a solution to integrate with the carrier Designing the strategy to develop a unified commercial insurance API to work with multiple carriers. Build features for enterprise customers that solve their unique needs while being easily re-useable across other customers Proactively identify opportunities to improve the quality, stability, and scalability of our systems. Conduct code reviews and provide helpful feedback that maintains our high code quality behind our systems Collaborate cross-functionally to solve business problems and continue to support our rapid growth What We Are Looking For We are looking for strong, independent engineers who would like to work in a fast-paced environment with lots of responsibility and scale. We have open roles for Backend and Frontend engineers. Ideal candidates will have prior startup experience and the ability to build systems from scratch. To succeed in this role, you have Strong ownership mentality – You take initiative, see projects through from start to finish, and treat the codebase and product as if you built the company yourself Exceptional communication skills – You can clearly articulate technical problems, propose solutions, and collaborate effectively across teams. You understand that in a startup, clear pro-active communication is as important as clean code Intellectual curiosity and learning agility – You're excited to dive into unfamiliar territory, whether it's insurance domain knowledge, a new carrier's API, or an emerging technology. You ask questions, seek to understand the "why," and continuously expand your skill set Comfort with ambiguity – You thrive in environments where requirements evolve, and you can navigate complex systems that require deep domain context Pragmatic approach to AI tooling – You actively leverage and experiment with the latest AI development tools (like Cursor, Claude, GitHub Copilot) to accelerate your work and aren't afraid to build on top of LLM APIs to solve business problems Quality-focused craftsmanship – You take pride in writing clean, maintainable code and understand that good testing empowers rather than burdens the team 3+ years of production software development experience – Ideally with backend systems (RESTful APIs, databases) and modern web technologies Nice To Have, But Not Essential Previous startup experience and understanding of the rapid pace and evolving priorities Production experience with our tech stack: Node, TypeScript, React, MongoDB Familiarity with AWS or other cloud environments Experience working with external APIs and third-party integrations What CoverForce Offers CoverForce has been a remote-first company in India since its inception and will always strive to be flexible to employees’ preferences. We know how to cultivate a successful and highly collaborative environment despite the distance. This includes: Quarterly virtual events to connect with your team members while celebrating our success and accomplishments Clear norms and etiquette around virtual meetings. Team building activities every month to let off steam and relax.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Skill enrichment (orchestrator / LLM)
ReactJS appears in high-volume job postings across frontend roles and is a standard hiring-pipeline requirement; its ecosystem and GitHub activity remain strong, indicating broad adoption.
Meta ·mit ·since 2013 (0.99)
ReactJS is a well-known, specific frontend library/framework name. In typical JDs it is unlikely to be confused with a different catalog skill.
Versioned 18
{
"React 0.10": "0.10",
"React 0.11": "0.11",
"React 0.12": "0.12",
"React 0.13": "0.13",
"React 0.14": "0.14",
"React 0.8": "0.8",
"React 0.9": "0.9",
"React 15": "15",
"React 16": "16",
"React 17": "17",
"React 18": "18",
"ReactJS 15": "15",
"ReactJS 16": "16",
"ReactJS 17": "17",
"ReactJS 18": "18"
}
Framework ·web_framework confidence 0.98
By the Tool vs Framework rule, ReactJS is something developers build applications with and it provides a structured application model, so it is a Framework.
- Category
- Framework
- Sub-category
- web_framework
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- SEPARATE_ENTITY
Dimensions (API 2 worklist)
-
Component Frameworks, Rendering, and UI Composition Proposed / LLM
Proposed / LLM dimension (no DB id yet)
Locked dimensions (v3 placement)
-
Component Frameworks, Rendering, and UI Composition
Pipeline tentative id
Frameworks and rendering models used to build reusable frontend UI components, compose screens and pages, and organize component-based application structure. Includes ReactJS and related patterns such as JSX, props, hooks, component composition, virtual DOM, rendering lifecycle, routing-oriented component structure, and framework-specific page/component composition patterns like Next.js.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Component Frameworks, Rendering, and UI Composition
d_merge_01
|
✓ | — | New skill saved · Existing dimension (reconciliation merge) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
Node.js appears in high-volume job postings across backend/full-stack roles and is a standard runtime in major cloud and tooling ecosystems, indicating broad hiring-pipeline adoption.
OpenJS Foundation ·mit ·since 2009 (0.98)
NodeJS is a well-known JavaScript runtime with a specific JD context. It is unlikely to be reasonably confused with another catalog skill in typical job descriptions.
Versioned 22
{
"Node 0.10": "0.10",
"Node 0.12": "0.12",
"Node 10": "10",
"Node 12": "12",
"Node 14": "14",
"Node 16": "16",
"Node 18": "18",
"Node 20": "20",
"Node 22": "22",
"Node 4": "4",
"Node 6": "6",
"Node 8": "8",
"Node.js 0.10": "0.10",
"Node.js 0.12": "0.12",
"Node.js 10": "10",
"Node.js 12": "12",
"Node.js 14": "14",
"Node.js 16": "16",
"Node.js 18": "18",
"Node.js 20": "20",
"Node.js 22": "22",
"Node.js 4": "4",
"Node.js 6": "6",
"Node.js 8": "8",
"NodeJS 14": "14",
"NodeJS 16": "16",
"NodeJS 18": "18",
"NodeJS 20": "20",
"NodeJS 22": "22"
}
Runtime ·javascript_runtime confidence 0.99
Node.js is an execution environment for running JavaScript code, so by the Runtime rule it is fundamentally a runtime rather than a tool or framework.
- Category
- Runtime
- Sub-category
- javascript_runtime
- Skill nature
- RUNTIME
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- SEPARATE_ENTITY
Dimensions (API 2 worklist)
-
Version Control Systems Catalog dimension db id 365
Library dimension (catalog)
Locked dimensions (v3 placement)
-
Node.js Runtime Development
Pipeline tentative id
Covers building server-side and tooling applications with Node.js, including its runtime model, package ecosystem, and common JavaScript/TypeScript backend patterns. NodeJS belongs here because it names the platform used to write and run these applications.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Version Control Systems
d_init_01
|
✓ | — | New skill saved · 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 skipped (dimension not under chosen role) |
|
NoSQL and Data Lake Storage
nosql-and-data-lake-storage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Java (CANONICAL) primary
- JDK (VERSION)
- JDK 10 (VERSION)
- JDK 11 (VERSION)
- JDK 12 (VERSION)
- JDK 13 (VERSION)
- JDK 14 (VERSION)
- JDK 15 (VERSION)
- JDK 16 (VERSION)
- JDK 17 (VERSION)
- JDK 18 (VERSION)
- JDK 19 (VERSION)
- JDK 20 (VERSION)
- JDK 21 (VERSION)
- JDK 5 (VERSION)
- JDK 6 (VERSION)
- JDK 7 (VERSION)
- JDK 8 (VERSION)
- JDK 9 (VERSION)
- Java 1.0 (VERSION)
- Java 1.1 (VERSION)
- Java 1.2 (VERSION)
- Java 1.3 (VERSION)
- Java 1.4 (VERSION)
- Java 1.5 (VERSION)
- Java 1.6 (VERSION)
- Java 1.7 (VERSION)
- Java 1.8 (VERSION)
- Java 10 (VERSION)
- Java 11 (VERSION)
- Java 12 (VERSION)
- Java 13 (VERSION)
- Java 14 (VERSION)
- Java 15 (VERSION)
- Java 16 (VERSION)
- Java 17 (VERSION)
- Java 18 (VERSION)
- Java 19 (VERSION)
- Java 20 (VERSION)
- Java 21 (VERSION)
- Java 5 (VERSION)
- Java 6 (VERSION)
- Java 7 (VERSION)
- Java 8 (VERSION)
- Java 9 (VERSION)
- Java11 (VERSION)
- Java17 (VERSION)
- Java21 (VERSION)
- Java8 (VERSION)
- OpenJDK 11 (VERSION)
- OpenJDK 17 (VERSION)
- OpenJDK 21 (VERSION)
- OpenJDK 8 (VERSION)
- java 11 (VERSION)
- java 17 (VERSION)
- java 21 (VERSION)
- java 4 (VERSION)
- java 5 (VERSION)
- java 6 (VERSION)
- java 7 (VERSION)
- java 8 (VERSION)
- java lts (VERSION)
- java-11 (VERSION)
- java-17 (VERSION)
- java-21 (VERSION)
- java-4 (VERSION)
- java-5 (VERSION)
- java-6 (VERSION)
- java-7 (VERSION)
- java-8 (VERSION)
- java11 (VERSION)
- java17 (VERSION)
- java21 (VERSION)
- java4 (VERSION)
- java5 (VERSION)
- java6 (VERSION)
- java7 (VERSION)
- java8 (VERSION)
- jdk 11 (VERSION)
- jdk 17 (VERSION)
- jdk 21 (VERSION)
- jdk 4 (VERSION)
- jdk 5 (VERSION)
- jdk 6 (VERSION)
- jdk 7 (VERSION)
- jdk 8 (VERSION)
- jdk11 (VERSION)
- jdk17 (VERSION)
- jdk21 (VERSION)
- jdk4 (VERSION)
- jdk5 (VERSION)
- jdk6 (VERSION)
- jdk7 (VERSION)
- jdk8 (VERSION)
- jvm21 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- Oracle
- License
- other_open
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 21
Maturity reasoning: Java is a hiring-pipeline staple with very high JD volume across enterprise backend, Android, and cloud roles; it remains widely supported by major vendors and frameworks like Spring.
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)
-
Frontend Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Frontend Engineer, Full Stack Developer
-
Programming Languages for AI Workflows Catalog dimension db id 261
Library dimension (catalog)
Roles linked in library: AI 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
-
ServiceNow Scripting and Logic Catalog dimension db id 210
Library dimension (catalog)
Roles linked in library: ServiceNOW Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Frontend Programming Languages
frontend-programming-languages
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | 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) |
|
ServiceNow Scripting and Logic
servicenow-scripting-and-logic
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Kotlin (CANONICAL) primary
- kotlin 1.9 (VERSION)
- kotlin 1.9.0 (VERSION)
- kotlin 1.9.1 (VERSION)
- kotlin 1.9.10 (VERSION)
- kotlin 1.9.x (VERSION)
- kotlin-1.9 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- JetBrains
- License
- apache_2
- Year introduced
- 2011
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Kotlin appears in many Android, backend, and multiplatform job postings, and JetBrains reports strong ecosystem growth; it’s a mainstream hiring skill rather than niche.
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)
-
Frontend Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Frontend Engineer, Full Stack Developer
-
Programming Languages for AI Workflows Catalog dimension db id 261
Library dimension (catalog)
Roles linked in library: AI 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 |
|---|---|---|---|
|
Frontend Programming Languages
frontend-programming-languages
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | 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
- 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
- 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
- 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 saved |
Skill enrichment (orchestrator / LLM)
APIs are a core hiring staple across backend, mobile, and platform JDs; REST/GraphQL/API design appears in large-volume job postings and vendor docs from AWS, Google, and Microsoft.
·since 1968 (0.98)
API is a standard, widely used technical term in JDs and is usually unambiguous in context; it is not typically confused with a different catalog skill.
Not versioned
Protocol ·application_programming_interface confidence 0.93
API is fundamentally a communication contract/interface between systems, so by the Protocol rule it fits best as a protocol-like standard for interaction rather than a tool or platform.
- Category
- Protocol
- Sub-category
- application_programming_interface
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- NOT_APPLICABLE
Dimensions (API 2 worklist)
-
API Consumption and Data Fetching Proposed / LLM
Proposed / LLM dimension (no DB id yet)
Locked dimensions (v3 placement)
-
API Consumption and Data Fetching
Pipeline tentative id
Client-side or frontend integration with backend services and third-party APIs to request, receive, and transform remote data for application use. Includes REST/API consumption, GraphQL queries, request/response handling, pagination, filtering, retries, error handling, JSON parsing, contract alignment, and shaping fetched data for UI consumption. Excludes API design, endpoint versioning, authentication protocol design, backend service implementation, database access, and event streaming.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Consumption and Data Fetching
d_merge_01
|
✓ | — | New skill saved · Existing dimension (reconciliation merge) · 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 |
|---|---|---|---|---|---|---|
| MongoDB | in_db |
NoSQL and Cache Stores
nosql-and-cache-stores
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MongoDB | in_db |
NoSQL and Data Lake Storage
nosql-and-data-lake-storage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Frontend Programming Languages
frontend-programming-languages
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| JavaScript | in_db |
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Programming Languages for Security Work
programming-languages-for-security-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
ServiceNow Scripting and Logic
servicenow-scripting-and-logic
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| TypeScript | in_db |
Frontend Programming Languages
frontend-programming-languages
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| TypeScript | in_db |
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| TypeScript | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| TypeScript | in_db |
Programming Languages for Test Automation
programming-languages-for-test-automation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| 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) | |
| 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) | |
| REST | in_db |
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| ReactJS | in_db |
Component Frameworks, Rendering, and UI Composition
d_merge_01
|
✓ | — | New skill saved · Existing dimension (reconciliation merge) · Role↔dimension skipped (dimension not under chosen role) | |
| NodeJS | in_db |
Version Control Systems
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| API | in_db |
API Consumption and Data Fetching
d_merge_01
|
✓ | — | New skill saved · Existing dimension (reconciliation merge) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_added | ReactJS | 2636 |
| canonical_skill_added | NodeJS | 2637 |
| canonical_skill_added | API | 2638 |
| dimension_skill_link | ReactJS ↔ Component Frameworks, Rendering, and UI Composition | 2 |
| dimension_skill_link | NodeJS ↔ Version Control Systems | 365 |
| dimension_skill_link | API ↔ API Consumption and Data Fetching | 9 |
API 1 — extract-from-jd click to toggle
{
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{
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{
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"skill_name": "REST"
},
{
"is_primary": false,
"skill_name": "API"
}
],
"run_id": null
}
API 2 — extract-details
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"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": "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"
},
"input_skill": "TypeScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
]
},
{
"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"
},
"input_skill": "TypeScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
]
},
{
"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"
},
"input_skill": "TypeScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Automation Tester",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "automation-tester",
"source": "db"
}
]
}
],
"input_skill": "TypeScript",
"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": "Docker",
"alias_type": "CANONICAL",
"id": 299,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 11,
"display_name": "Docker",
"id": 153,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "docker",
"sub_category_id": 170,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"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"
},
"input_skill": "Docker",
"llm_role": null,
"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"
}
]
},
{
"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"
},
"input_skill": "Docker",
"llm_role": null,
"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"
}
]
}
],
"input_skill": "Docker",
"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": "AWS",
"alias_type": "CANONICAL",
"id": 348,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 13,
"display_name": "AWS",
"id": 163,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "aws",
"sub_category_id": 161,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"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"
},
"input_skill": "AWS",
"llm_role": null,
"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"
}
]
},
{
"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"
},
"input_skill": "AWS",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cybersecurity Engineer",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
}
],
"input_skill": "AWS",
"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": "REST",
"alias_type": "CANONICAL",
"id": 266,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "REST",
"id": 121,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "rest",
"sub_category_id": 67,
"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": "REST",
"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"
}
]
}
],
"input_skill": "REST",
"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": [],
"canonical": null,
"dimensions": [
{
"dimension": {
"difficulty_hint": null,
"display_name": "API Consumption and Data Fetching",
"id": null,
"rationale": "Client-side or frontend integration with backend services and third-party APIs to request, receive, and transform remote data for application use. Includes REST/API consumption, GraphQL queries, request/response handling, pagination, filtering, retries, error handling, JSON parsing, contract alignment, and shaping fetched data for UI consumption. Excludes API design, endpoint versioning, authentication protocol design, backend service implementation, database access, and event streaming.",
"slug": "d_merge_01",
"source": "llm"
},
"input_skill": "API",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "API",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Protocol",
"skill_nature": "PROTOCOL",
"sub_category": "application_programming_interface",
"typical_lifespan": "EVERGREEN",
"version_strategy": "NOT_APPLICABLE",
"volatility": "STABLE"
},
"enrichment": {
"ambiguity": {
"ambiguity_flag": false,
"confused_with": [],
"reasoning": "API is a standard, widely used technical term in JDs and is usually unambiguous in context; it is not typically confused with a different catalog skill."
},
"context_keywords": {
"context_keywords": [
"REST",
"GraphQL",
"OpenAPI",
"Swagger",
"endpoint",
"webhook",
"JSON",
"OAuth 2.0",
"API gateway",
"rate limiting",
"pagination",
"versioning",
"SDK",
"microservices",
"HTTP"
]
},
"maturity": {
"confidence": 0.97,
"maturity": "well_known",
"reasoning": "APIs are a core hiring staple across backend, mobile, and platform JDs; REST/GraphQL/API design appears in large-volume job postings and vendor docs from AWS, Google, and Microsoft."
},
"skill_id": "api",
"vendor_license": {
"confidence": 0.98,
"license": null,
"vendor": null,
"year_introduced": 1968
},
"versioning": {
"current_version": null,
"version_aliases": {},
"versioned": false
}
},
"keep_log": [],
"locked_dimensions": [
{
"description": "Client-side or frontend integration with backend services and third-party APIs to request, receive, and transform remote data for application use. Includes REST/API consumption, GraphQL queries, request/response handling, pagination, filtering, retries, error handling, JSON parsing, contract alignment, and shaping fetched data for UI consumption. Excludes API design, endpoint versioning, authentication protocol design, backend service implementation, database access, and event streaming.",
"exemplar_skills": [
"API Consumption and Data Fetching"
],
"in_scope": "Skills, tools, and practices that belong under API Consumption and Data Fetching for the target role, including items implied by the dimension rationale.",
"name": "API Consumption and Data Fetching",
"out_of_scope": "Adjacent clusters explicitly not owned by API Consumption and Data Fetching, including unrelated platforms, roles, and skill families per library policy.",
"overlap_flags": [],
"tentative_id": "d_merge_01"
}
],
"merge_log": [
{
"a_dim_id": "api-integration-and-data-fetching",
"a_name": "API Integration and Data Fetching",
"a_role": "__skill_focal__",
"b_dim_id": "api-integration-and-data-fetching",
"b_name": "API Integration and Data Fetching",
"b_role": "Full Stack Developer",
"into": "d_merge_01",
"into_name": "API Consumption and Data Fetching",
"merged_from": [
"api-integration-and-data-fetching",
"api-integration-and-data-fetching"
],
"pair_kind": "cross_role",
"reasoning": "Both dimensions describe the same client-side/API-consumption cluster, not different skills. Dim A explicitly says it is about \"client-side use of APIs to request, receive, and shape data\" and excludes API design/backend implementation; its exemplars are REST API consumption, GraphQL queries, JSON parsing, pagination handling, and HTTP error handling. Dim B says essentially the same thing for frontend applications: \"connecting frontend applications to backend services and third-party endpoints\" with request orchestration, error handling, pagination, and shaping remote data for UI consumption. The wording differs, but the substance and exemplar skills overlap almost completely, and the cross-role label here does not indicate a role-specific distinction in the underlying skill cluster.",
"similarity": 0.7530536391953782
}
],
"placed": {
"name": "API",
"placement_confidence": 0.92,
"primary_dimension": "d_merge_01",
"reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
"secondary_dimensions": [],
"skill_id": "api"
},
"relationships": {
"child_skills": [],
"parent_skills": [],
"related_to": [
"rest-apis",
"tls",
"owasp-top-10",
"web3-js",
"infura",
"alchemy",
"truffle",
"dex",
"token-uri",
"polygon"
],
"requires": [],
"skill_id": "api",
"suppress_on_match": []
},
"skill_id": "api",
"split_log": [],
"typed": {
"alternatives_considered": [],
"confidence": 0.93,
"name": "API",
"reasoning": "API is fundamentally a communication contract/interface between systems, so by the Protocol rule it fits best as a protocol-like standard for interaction rather than a tool or platform.",
"skill_id": "api",
"subtype": "application_programming_interface",
"type": "Protocol"
},
"warnings": [
"stage3_post_filter_dropped_catalog_only_locked_dims:40-\u003e1"
]
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"ReactJS",
"NodeJS",
"API"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Full Stack Developer",
"id": 2,
"rationale": "The primary skills involve both front-end (ReactJS, JavaScript, TypeScript) and back-end (NodeJS, MongoDB) technologies.",
"role_archetype": null,
"slug": "full-stack-developer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "ReactJS",
"tag": "new"
},
{
"skill": "NodeJS",
"tag": "new"
},
{
"skill": "MongoDB",
"tag": "in_db"
},
{
"skill": "JavaScript",
"tag": "in_db"
},
{
"skill": "TypeScript",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "REST",
"tag": "in_db"
},
{
"skill": "API",
"tag": "new"
}
],
"persistence": {
"items": [
{
"chosen_role_id": 2,
"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": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"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": 2,
"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": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Frontend Programming Languages",
"id": 1,
"rationale": "Languages used to implement browser-side application logic, component behavior, and UI state. This is the core code layer for frontend features and interactive experiences.",
"slug": "frontend-programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "JavaScript",
"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": "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": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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": "JavaScript",
"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": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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": "JavaScript",
"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": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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": "JavaScript",
"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": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ServiceNow Scripting and Logic",
"id": 210,
"rationale": "Server-side scripting used to implement workflow behavior, validations, and record logic on the ServiceNow platform. This is the core customization layer for translating requirements into executable platform behavior.",
"slug": "servicenow-scripting-and-logic",
"source": "db"
},
"dimension_id": 210,
"input_skill": "JavaScript",
"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": "ServiceNOW Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "servicenow-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Frontend Programming Languages",
"id": 1,
"rationale": "Languages used to implement browser-side application logic, component behavior, and UI state. This is the core code layer for frontend features and interactive experiences.",
"slug": "frontend-programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "TypeScript",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
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"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Full Stack Developer",
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],
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{
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"dimension": {
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"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.",
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"source": "db"
},
"dimension_id": 261,
"input_skill": "TypeScript",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
"display_name": "AI Engineer",
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}
],
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{
"chosen_role_id": 2,
"dimension": {
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"display_name": "Programming Languages for ML Systems",
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"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": "TypeScript",
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"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",
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],
"skill_dimension_saved": true,
"skill_id": 2,
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{
"chosen_role_id": 2,
"dimension": {
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"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": "TypeScript",
"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",
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}
],
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"skill_id": 2,
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{
"chosen_role_id": 2,
"dimension": {
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"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",
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"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 153,
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},
{
"chosen_role_id": 2,
"dimension": {
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"display_name": "Model Serving Deployment and Runtime Packaging",
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"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",
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},
{
"display_name": "Machine Learning Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 153,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
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"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",
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"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",
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}
],
"skill_dimension_saved": true,
"skill_id": 163,
"skill_tag": "in_db",
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},
{
"chosen_role_id": 2,
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"display_name": "Cloud Security Platforms",
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"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",
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"rationale": null,
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"slug": "cybersecurity-engineer",
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}
],
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"skill_id": 163,
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{
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"display_name": "API Integration and Data Fetching",
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"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": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
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{
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"slug": "frontend-engineer",
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},
{
"display_name": "Full Stack Developer",
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"rationale": null,
"role_archetype": null,
"slug": "full-stack-developer",
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],
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"skill_tag": "in_db",
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{
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"display_name": "Component Frameworks, Rendering, and UI Composition",
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"rationale": "Frameworks and rendering models used to build reusable frontend UI components, compose screens and pages, and organize component-based application structure. Includes ReactJS and related patterns such as JSX, props, hooks, component composition, virtual DOM, rendering lifecycle, routing-oriented component structure, and framework-specific page/component composition patterns like Next.js.",
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"source": "llm"
},
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"input_skill": "ReactJS",
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"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 Existing dimension (reconciliation merge) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2636,
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},
{
"chosen_role_id": 2,
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"display_name": "Version Control Systems",
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"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": "NodeJS",
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"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 2637,
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{
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"display_name": "API Consumption and Data Fetching",
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"source": "llm"
},
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"input_skill": "API",
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"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 Existing dimension (reconciliation merge) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
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}
],
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.