Pipeline run
5fe1b1d3-985f-42b6-8256-74c3da2d27d6
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
v3 pipeline · Full Stack Engineer
approved1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Full Stack Engineer
CASE Fslug: full-stack-engineer · id: 15 · source: db
The primary skills involve both frontend and backend technologies, making Full Stack Engineer the best fit.
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
About the job Inception, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visitwww.inceptionai.ai Role Overview The Full Stack Engineer at Inception is responsible for designing, developing, and maintaining scalable, end-to-end software systems that enable seamless data and service integration. The role involves building high-performance front-end and back-end systems, ensuring robust architecture, and delivering reliable, production-ready applications. This role is a full-time position based in India (remote). Key Responsibilities • Design and develop responsive, high-performance front-end applications using Next.js, translating UI/UX designs into scalable solutions • Build and maintain backend services and APIs using Python (FastAPI/Flask), ensuring performance, scalability, and reliability • Architect end-to-end solutions across frontend, backend, databases, and integration layers • Design, develop, and optimize RESTful APIs and service interfaces to support product functionality • Ensure non-functional requirements (performance, security, scalability, maintainability) are embedded in all solutions • Develop and manage relational and NoSQL databases, ensuring efficient data storage and retrieval • Contribute to system architecture decisions, including monolithic and microservices-based approaches • Collaborate with data scientists, applied scientists, and engineering teams to integrate AI capabilities into applications • Troubleshoot, debug, and resolve issues across the full technology stack • Participate in code reviews and enforce best practices for code quality, testing, and documentation Qualifications • Bachelor’s or Master’s degree in Computer Science or related field • Strong experience in Python and backend frameworks (FastAPI or Flask) • Experience building frontend applications using Next.js / React ecosystem • Strong knowledge of API design and distributed systems • Experience with relational and NoSQL databases • Familiarity with Docker/Kubernetes and cloud platforms (preferably Azure) • Experience with version control (Git) and modern development practices The successful candidate will be engaged via an external workforce partner in line with Inception’s operating model in the region.
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
- Next.js (CANONICAL) primary
- Next 10 (VERSION)
- Next 11 (VERSION)
- Next 12 (VERSION)
- Next 13 (VERSION)
- Next 14 (VERSION)
- Next 15 (VERSION)
- Next 2 (VERSION)
- Next 3 (VERSION)
- Next 4 (VERSION)
- Next 5 (VERSION)
- Next 6 (VERSION)
- Next 7 (VERSION)
- Next 8 (VERSION)
- Next 9 (VERSION)
- Next.js 1 (VERSION)
- Next.js 10 (VERSION)
- Next.js 11 (VERSION)
- Next.js 12 (VERSION)
- Next.js 13 (VERSION)
- Next.js 14 (VERSION)
- Next.js 15 (VERSION)
- Next.js 2 (VERSION)
- Next.js 3 (VERSION)
- Next.js 4 (VERSION)
- Next.js 5 (VERSION)
- Next.js 6 (VERSION)
- Next.js 7 (VERSION)
- Next.js 8 (VERSION)
- Next.js 9 (VERSION)
- next (VERSION)
- next.js (VERSION)
- next.js 14 (VERSION)
- nextjs (VERSION)
- nextjs 14 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Web Framework
- Vendor
- Vercel
- License
- mit
- Year introduced
- 2016
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Next.js appears in many frontend/full-stack job descriptions and is a common React meta-framework for production apps; Vercel’s ecosystem and strong GitHub adoption signal broad market demand.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 35
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Meta-Frameworks & SSR Catalog dimension db id 130
Library dimension (catalog)
Roles linked in library: Frontend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Meta-Frameworks & SSR
meta-frameworks-ssr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Python (CANONICAL) primary
- Python 2 (VERSION)
- Python 2.x (VERSION)
- Python 3 (VERSION)
- Python 3.10 (VERSION)
- Python 3.11 (VERSION)
- Python 3.12 (VERSION)
- Python 3.x (VERSION)
- py (VERSION)
- py2 (VERSION)
- py3 (VERSION)
- python 3 (VERSION)
- python 3.x (VERSION)
- python2 (VERSION)
- python3 (VERSION)
- python3.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- PSF
- License
- mit
- Year introduced
- 1991
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3
Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 416
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Engineer
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cybersecurity Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
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 XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- FastAPI (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Web Framework
- Vendor
- Sebastián Ramírez
- License
- mit
- Year introduced
- 2018
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: FastAPI appears in many Python backend job postings and has strong GitHub adoption; it’s now a common choice for API development alongside Flask/Django rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 35
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
Flask appears in many Python web backend job postings and remains a common lightweight framework in hiring pipelines, alongside strong GitHub usage and ecosystem activity.
Pallets Projects ·bsd ·since 2010 (0.95)
“Flask” in JDs typically refers specifically to the Python web microframework; unlikely to be confused with other catalog skills.
Versioned 3.x
{
"flask 2": "2.x",
"flask 2.x": "2.x",
"flask 3": "3.x",
"flask 3.x": "3.x",
"flask2": "2.x",
"flask3": "3.x",
"flask\u003e=3": "3.x"
}
Framework ·web_framework confidence 0.99
Flask is a lightweight web framework that you build applications inside, so it fits the Framework rule rather than a Tool or Library.
- Category
- Framework
- Sub-category
- web_framework
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- SEPARATE_ENTITY
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
Locked dimensions (v3 placement)
-
Python Web Application Frameworks
Pipeline tentative id
Frameworks used to build server-side web applications, APIs, and request/response handling in Python. Flask belongs here because it is a Python microframework for routing, middleware, templating, and web service development.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- REST (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Api Architecture Style
- Year introduced
- 2000
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: REST is a default API architecture in many job descriptions and is widely supported by major vendors/frameworks; OpenAPI and RESTful endpoints remain standard in hiring pipelines.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 10
- Sub-category id
- 48
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Design and Contracts Catalog dimension db id 3
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Design and Contracts
api-design-and-contracts
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
Relational databases remain a hiring staple across most backend/data JDs, with PostgreSQL, MySQL, and SQL Server appearing routinely; cloud vendors also center managed RDBMS offerings, signaling broad adoption.
(0.90)
“Relational Databases” is a clear domain term (SQL/relational DBs) and is unlikely to be confused with other distinct catalog skills.
Not versioned
Domain ·relational_database_management confidence 0.90
Relational Databases is a vertical body of knowledge about the relational data model and database systems, so it fits the Domain type rather than a specific datastore product.
- Category
- Domain
- Sub-category
- relational_database_management
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- NOT_APPLICABLE
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
Locked dimensions (v3 placement)
-
Relational Database Systems
Pipeline tentative id
Relational database systems used to store, query, and manage structured data with tables, schemas, keys, and SQL. This skill belongs here because it covers the core database technology and operational concepts behind application data storage.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
(0.95)
“NoSQL” is a widely used, specific database paradigm term; typical JDs won’t confuse it with other distinct skills in the catalog.
Not versioned
Concept ·database_paradigm confidence 0.93
NoSQL is fundamentally a knowledge unit describing a class of non-relational database approaches, so it fits the Concept type rather than a specific datastore or tool.
- Category
- Concept
- Sub-category
- database_paradigm
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- NOT_APPLICABLE
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Engineer
Locked dimensions (v3 placement)
-
NoSQL Databases
Pipeline tentative id
Non-relational database systems used for flexible schemas, horizontal scaling, and workload-specific data access patterns. NoSQL belongs here because it refers to the database family rather than a single product or query language.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
NoSQL Databases
d_init_01
|
✓ | — | New skill saved · Existing dimension (embedding dedup) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- microservices (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Architecture
- Sub-category
- Distributed System Architecture
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 1
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Microservices and Distributed Systems Catalog dimension db id 9
Library dimension (catalog)
Roles linked in library: Backend Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
AI appears in a large and growing share of job descriptions across software, data, and product roles; major vendors like Microsoft, Google, and AWS have broad AI offerings and hiring demand reflects mainstream adoption.
(1.00)
Could be confused with: ml
“AI” in JDs is often used interchangeably with “ML” (machine learning), so an extractor may map it to the ML skill.
Not versioned
Concept ·artificial_intelligence confidence 0.98
AI is fundamentally a named knowledge unit about intelligent systems, so it fits the Concept category rather than a tool, platform, or methodology.
- Category
- Concept
- Sub-category
- artificial_intelligence
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- NOT_APPLICABLE
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
Locked dimensions (v3 placement)
-
Artificial Intelligence Concepts
Pipeline tentative id
Core concepts, capabilities, and terminology for building or using AI systems. The skill AI is too broad to map cleanly to a narrower catalog entry, so this dimension captures the general AI knowledge base.
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Code Review (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- SoftSkill
- Sub-category
- Code Review
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Code review is a standard hiring-pipeline requirement in engineering JDs and is built into major platforms like GitHub/GitLab pull-request workflows, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- PRACTICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 58
- Sub-category id
- 364
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | 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 |
|---|---|---|---|---|---|---|
| Next.js | in_db |
Meta-Frameworks & SSR
meta-frameworks-ssr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| 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 XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| FastAPI | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| REST | in_db |
API Design and Contracts
api-design-and-contracts
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Microservices | in_db |
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Code Review | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Flask | in_db |
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Relational Databases | in_db |
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AI | in_db |
React Frontend Development
d_init_01
|
✓ | — | New skill saved · Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| NoSQL | in_db |
NoSQL Databases
d_init_01
|
✓ | — | New skill saved · Existing dimension (embedding dedup) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_added | Flask | 1344 |
| canonical_skill_added | Relational Databases | 1345 |
| canonical_skill_added | NoSQL | 1346 |
| canonical_skill_added | AI | 1347 |
| dimension_skill_link | Flask ↔ React Frontend Development | 96 |
| dimension_skill_link | Relational Databases ↔ React Frontend Development | 96 |
| dimension_skill_link | NoSQL ↔ NoSQL Databases | 19 |
| dimension_skill_link | AI ↔ React Frontend Development | 96 |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Inception, a G42 company, is",
"last_5_words": "creating positive societal impact."
},
"text": "Inception, a G42 company, is the region\u2019s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer \u2013 transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact.",
"word_count": 64
},
"certifications": [],
"company_name": "Inception",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO",
"Tech Consulting"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/BSC - Computer Science (or related)",
"raw": "Bachelor\u2019s or Master\u2019s degree in Computer Science or related field",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": null,
"raw": null
},
"job_locations": [
{
"aliases": [],
"city": null,
"country": "India",
"state": null,
"work_mode": "remote"
}
],
"role": "Full Stack Engineer",
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Role Overview",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The Full Stack Engineer at",
"last_5_words": "production-ready applications."
},
"text": "The Full Stack Engineer at Inception is responsible for designing, developing, and maintaining scalable, end-to-end software systems that enable seamless data and service integration. The role involves building high-performance front-end and back-end systems, ensuring robust architecture, and delivering reliable, production-ready applications.",
"word_count": 49
},
{
"bullet_count": 10,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Design and develop responsive,",
"last_5_words": "quality, testing, and documentation"
},
"text": "\u2022 Design and develop responsive, high-performance front-end applications using Next.js, translating UI/UX designs into scalable solutions\n\n \u2022 Build and maintain backend services and APIs using Python (FastAPI/Flask), ensuring performance, scalability, and reliability\n\n \u2022 Architect end-to-end solutions across frontend, backend, databases, and integration layers\n\n \u2022 Design, develop, and optimize RESTful APIs and service interfaces to support product functionality\n\n \u2022 Ensure non-functional requirements (performance, security, scalability, maintainability) are embedded in all solutions\n\n \u2022 Develop and manage relational and NoSQL databases, ensuring efficient data storage and retrieval\n\n \u2022 Contribute to system architecture decisions, including monolithic and microservices-based approaches\n\n \u2022 Collaborate with data scientists, applied scientists, and engineering teams to integrate AI capabilities into applications\n\n \u2022 Troubleshoot, debug, and resolve issues across the full technology stack\n\n \u2022 Participate in code reviews and enforce best practices for code quality, testing, and documentation",
"word_count": 203
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Next.js"
},
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "FastAPI"
},
{
"is_primary": true,
"skill_name": "Flask"
},
{
"is_primary": true,
"skill_name": "REST"
},
{
"is_primary": true,
"skill_name": "Relational Databases"
},
{
"is_primary": true,
"skill_name": "NoSQL"
},
{
"is_primary": false,
"skill_name": "Microservices"
},
{
"is_primary": false,
"skill_name": "AI"
},
{
"is_primary": false,
"skill_name": "Code Review"
}
],
"jd_role": {
"display_name": "Full Stack Engineer",
"rationale": null,
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Inception, a G42 company, is",
"last_5_words": "creating positive societal impact."
},
"text": "Inception, a G42 company, is the region\u2019s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer \u2013 transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact.",
"word_count": 64
},
"certifications": [],
"company_name": "Inception",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO",
"Tech Consulting"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
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API 2 — extract-details
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"in_scope": "NoSQL, document databases, key-value stores, wide-column databases, graph databases, MongoDB, Cassandra, DynamoDB, Redis persistence, Couchbase, schema-less modeling, partitioning, replication, eventual consistency",
"name": "NoSQL Databases",
"out_of_scope": "SQL relational databases, ORM usage, data warehousing, stream processing, in-memory caching without persistence, which belong to other database or data platform dimensions",
"overlap_flags": [
{
"reason": "Managed NoSQL services are often delivered through cloud platforms, but the database model itself is the core skill here.",
"with_dim_id": "cloud-platforms",
"with_dim_name": null,
"with_role": "Backend Engineer, Cybersecurity Engineer, Data Engineer, DevOps Engineer, ML Engineer"
}
],
"tentative_id": "d_init_01"
}
],
"merge_log": [],
"placed": {
"name": "NoSQL",
"placement_confidence": 0.92,
"primary_dimension": "d_init_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": "nosql"
},
"relationships": {
"child_skills": [],
"parent_skills": [],
"related_to": [
"vector-db",
"firebase-firestore",
"sqlite",
"managed-databases",
"rds",
"databricks",
"kubernetes",
"microsoft-azure"
],
"requires": [],
"skill_id": "nosql",
"suppress_on_match": []
},
"skill_id": "nosql",
"split_log": [],
"typed": {
"alternatives_considered": [],
"confidence": 0.93,
"name": "NoSQL",
"reasoning": "NoSQL is fundamentally a knowledge unit describing a class of non-relational database approaches, so it fits the Concept type rather than a specific datastore or tool.",
"skill_id": "nosql",
"subtype": "database_paradigm",
"type": "Concept"
},
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "microservices",
"alias_type": "CANONICAL",
"id": 178,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 1,
"display_name": "microservices",
"id": 41,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PATTERN",
"slug": "microservices",
"sub_category_id": 1,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Microservices and Distributed Systems",
"id": 9,
"rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
"slug": "microservices-and-distributed-systems",
"source": "db"
},
"input_skill": "Microservices",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
]
}
],
"input_skill": "Microservices",
"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": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "AI",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "AI",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concept",
"skill_nature": "CONCEPT",
"sub_category": "artificial_intelligence",
"typical_lifespan": "EVERGREEN",
"version_strategy": "NOT_APPLICABLE",
"volatility": "STABLE"
},
"enrichment": {
"ambiguity": {
"ambiguity_flag": true,
"confused_with": [
"ml"
],
"reasoning": "\u201cAI\u201d in JDs is often used interchangeably with \u201cML\u201d (machine learning), so an extractor may map it to the ML skill."
},
"context_keywords": {
"context_keywords": [
"machine learning",
"neural networks",
"deep learning",
"natural language processing",
"computer vision",
"reinforcement learning",
"TensorFlow",
"PyTorch",
"data preprocessing",
"model training",
"predictive analytics",
"AI ethics",
"algorithm optimization",
"feature engineering",
"supervised learning"
]
},
"maturity": {
"confidence": 0.93,
"maturity": "well_known",
"reasoning": "AI appears in a large and growing share of job descriptions across software, data, and product roles; major vendors like Microsoft, Google, and AWS have broad AI offerings and hiring demand reflects mainstream adoption."
},
"skill_id": "ai",
"vendor_license": {
"confidence": 1.0,
"license": null,
"vendor": null,
"year_introduced": null
},
"versioning": {
"current_version": null,
"version_aliases": {},
"versioned": false
}
},
"keep_log": [],
"locked_dimensions": [
{
"description": "Core concepts, capabilities, and terminology for building or using AI systems. The skill AI is too broad to map cleanly to a narrower catalog entry, so this dimension captures the general AI knowledge base.",
"exemplar_skills": [
"AI",
"machine learning",
"generative AI",
"model inference",
"prompt engineering"
],
"in_scope": "AI, machine learning basics, model capabilities and limits, supervised and unsupervised learning, inference concepts, generative AI concepts, prompt-based interaction, evaluation basics",
"name": "Artificial Intelligence Concepts",
"out_of_scope": "Specific ML frameworks and libraries, distributed training infrastructure, MLOps pipelines, AI governance/compliance, cloud platform services",
"overlap_flags": [
{
"reason": "Practical implementation of AI often overlaps with model-building libraries and training workflows.",
"with_dim_id": "ml-frameworks-and-libraries",
"with_dim_name": null,
"with_role": "ML Engineer"
},
{
"reason": "Operationalizing AI models can involve automated training, testing, and deployment pipelines.",
"with_dim_id": "ci-cd-for-machine-learning",
"with_dim_name": null,
"with_role": "ML Engineer"
},
{
"reason": "AI solutions may require governance review depending on the use case and risk profile.",
"with_dim_id": "ai-use-case-compliance-review",
"with_dim_name": null,
"with_role": "AI Compliance Officer"
}
],
"tentative_id": "d_init_01"
}
],
"merge_log": [],
"placed": {
"name": "AI",
"placement_confidence": 0.92,
"primary_dimension": "d_init_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": "ai"
},
"relationships": {
"child_skills": [],
"parent_skills": [],
"related_to": [
"intelligent-automation",
"algorithms",
"chatbots",
"virtual-assistants",
"openai",
"anthropic",
"faiss",
"crewai"
],
"requires": [],
"skill_id": "ai",
"suppress_on_match": []
},
"skill_id": "ai",
"split_log": [],
"typed": {
"alternatives_considered": [],
"confidence": 0.98,
"name": "AI",
"reasoning": "AI is fundamentally a named knowledge unit about intelligent systems, so it fits the Concept category rather than a tool, platform, or methodology.",
"skill_id": "ai",
"subtype": "artificial_intelligence",
"type": "Concept"
},
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Code Review",
"alias_type": "CANONICAL",
"id": 864,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 58,
"display_name": "Code Review",
"id": 516,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PRACTICE",
"slug": "code-review",
"sub_category_id": 364,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Code Review",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Code Review",
"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": [
"Flask",
"Relational Databases",
"NoSQL",
"AI"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Full Stack Engineer",
"id": 15,
"rationale": "The primary skills involve both frontend and backend technologies, making Full Stack Engineer the best fit.",
"role_archetype": "Engineering role focused on both frontend and backend development.",
"slug": "full-stack-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Next.js",
"tag": "in_db"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "FastAPI",
"tag": "in_db"
},
{
"skill": "Flask",
"tag": "new"
},
{
"skill": "REST",
"tag": "in_db"
},
{
"skill": "Relational Databases",
"tag": "new"
},
{
"skill": "NoSQL",
"tag": "new"
},
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "AI",
"tag": "new"
},
{
"skill": "Code Review",
"tag": "in_db"
}
],
"persistence": {
"items": [
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Meta-Frameworks \u0026 SSR",
"id": 130,
"rationale": "Frameworks that build on UI libraries to provide routing, server-side rendering, and static site generation.",
"slug": "meta-frameworks-ssr",
"source": "db"
},
"dimension_id": 130,
"input_skill": "Next.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": [
{
"display_name": "Frontend Engineer",
"id": 7,
"rationale": null,
"role_archetype": null,
"slug": "frontend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 705,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Core server-side languages used to implement backend business logic, integrations, and service internals. This is the primary coding surface for the role across application layers.",
"slug": "programming-languages",
"source": "db"
},
"dimension_id": 1,
"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": "Backend Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"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": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"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": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 39,
"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": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"dimension_id": 97,
"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": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"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": [],
"skill_dimension_saved": true,
"skill_id": 1201,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Design and Contracts",
"id": 3,
"rationale": "Designing and maintaining service interfaces that other systems consume. Covers endpoint shape, payload modeling, versioning, pagination, idempotency, and compatibility rules.",
"slug": "api-design-and-contracts",
"source": "db"
},
"dimension_id": 3,
"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": "Backend Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 11,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Microservices and Distributed Systems",
"id": 9,
"rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
"slug": "microservices-and-distributed-systems",
"source": "db"
},
"dimension_id": 9,
"input_skill": "Microservices",
"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": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 41,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Code Review",
"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": 516,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Flask",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 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": 1344,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Relational Databases",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 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": 1345,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"dimension_id": 19,
"input_skill": "NoSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1346,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "AI",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 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": 1347,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": null,
"rationale": "Non-relational database systems used for flexible schemas, horizontal scaling, and workload-specific data access patterns. NoSQL belongs here because it refers to the database family rather than a single product or query language.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": 19,
"input_skill": "NoSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "New skill saved \u00b7 Existing dimension (embedding dedup) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 1346,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 4,
"role_dimension_saved": 0,
"skill_dimension_saved": 4,
"skipped": 0
},
"planner_output": null,
"run_id": "5fe1b1d3-985f-42b6-8256-74c3da2d27d6"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.