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Pipeline run

7966f25e-ddd5-4924-bc17-1dd016791994

Pipeline LLM cost (USD)
API 1: $0.0062 API 2: $0.0001 API 3: $0.0000 Total: $0.0063

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data pipeline development
Design and maintain large-scale Datastage ETL batch pipelines and SQL-based data warehouse jobs, working with stakeholders to translate requirements into technical solutions and support Agile delivery, scheduling, and issue resolution.
""designing and developing large scale, distributed data processing pipelines using Datastage related technologies.""
Tech stack maturity
Mainstream Legacy cache hit
The profile centers on SQL and agile, which are widely used, long-established technologies and practices rather than cloud-native or bleeding-edge stacks.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (5)
Datastage SQL Agile Unix shell scripting CP4D
Skill cluster (2 dimension groups, role-scoped)
Programming Languages for Data Work
SQL
Cross-cutting / unaligned
Datastage Agile Unix shell scripting CP4D
Show KRA description ↓
CP4D, Unix shell scripting , Datastage , SQL - At least 6+ years of experience in designing and developing large scale, distributed data processing pipelines using Datastage related technologies. - Having expertise in Datastage ETL Batch processing - Expericence with Data warehousing and ETL concepts and techniques - UNIX shell scripting will be an added advantage in scheduling/running application jobs. - Experience with cloud pak for data will be added advantage - At least 5 years of experience in Project development life cycle activities and development/maintenance projects - Work with business stakeholders and other SMEs to understand high level business requirements. - Work with the Solution Designers and contribute to the development of project plans by participating in the scoping and estimating of proposed project. - Apply technical background understanding, business knowledge, system knowledge in the elicitation of Systems Requirements for projects. - Work in an Agile environment and participation in scrum daily standups, sprint planning reviews and retrospectives. - Understand project requirements and translate them into technical solutions which meets the project quality standards - Ability to work in team in diverse/multiple stakeholder environment and collaborate with upstream/downstream functional teams to identify, troubleshoot and resolve data issues. - Strong problem solving and Positive Analytical skills. - Excellent verbal and written communication skills. - Experience and desire to work in a Global delivery environment. - Stay up to date with new technologies and industry trends in Development.

Signals

Skill engineering-manager
0.67
Alias
KRA data-engineer
0.54

Post-classification

Centroidupdated · n=529
Alias collision log
New-role queue
New skills captured3
New KRA captured

Captured for admin review

Datastage primary Data Engineer pending
Unix shell scripting Data Engineer pending
CP4D Data Engineer pending
Status: completed Created: 2026-07-28T17:13:49.595489Z Updated: 2026-07-30T21:29:14.600241Z API 3 duration: 177 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

CASE D

slug: data-engineer · id: 2 · source: db

LLM2 picked data-engineer (confidence 0.87)

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
1
Skipped

Job description

Job description
Job Location- Hyderabad, Pune, Chennai, Bangalore, Trivandrum

Must have skills -CP4D, Unix shell scripting , Datastage , SQL

Significant :

Notice period : Immediate to 15-30 days ONLY.

Candidates serving Notice period will be preferred.

Please note - There should not be Career Gap more than 6 months(No Career Break)

Graduation score should be 60% & above

BGV (Background Verification)is mandatory.

- At least 6+ years of experience in designing and developing large scale, distributed data processing pipelines using Datastage related technologies.
- Having expertise in Datastage ETL Batch processing
- Expericence with Data warehousing and ETL concepts and techniques
- UNIX shell scripting will be an added advantage in scheduling/running application jobs.
- Experience with cloud pak for data will be added advantage
- At least 5 years of experience in Project development life cycle activities and development/maintenance projects
- Work with business stakeholders and other SMEs to understand high level business requirements.
- Work with the Solution Designers and contribute to the development of project plans by participating in the scoping and estimating of proposed project.
- Apply technical background understanding, business knowledge, system knowledge in the elicitation of Systems Requirements for projects.
- Work in an Agile environment and participation in scrum daily standups, sprint planning reviews and retrospectives.
- Understand project requirements and translate them into technical solutions which meets the project quality standards
- Ability to work in team in diverse/multiple stakeholder environment and collaborate with upstream/downstream functional teams to identify, troubleshoot and resolve data issues.
- Strong problem solving and Positive Analytical skills.
- Excellent verbal and written communication skills.
- Experience and desire to work in a Global delivery environment.
- Stay up to date with new technologies and industry trends in Development. .

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Datastage Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ISO/IEC
License
unknown
Year introduced
1986
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL is a hiring-pipeline staple across data, backend, and analytics roles; it appears in a very high volume of job descriptions and remains the standard query language for relational databases.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, WordPress Dev

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
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 saved
Unix shell scripting Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Bash scripting id=193 · bash-scripting

Aliases — catalog

  • Bash scripting (CANONICAL) primary

Context tags (catalog)

POSIX automation awk bash_profile bashrc chmod command_line cron environment variables exit codes functions grep here-doc pipes redirection scripts sed shebang shell stdin stdout text_processing variables xargs

Stored enrichment (catalog DB)

Category
Language
Sub-category
Shell Scripting Language
Vendor
GNU Project
License
gpl_v3
Year introduced
1989
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Bash scripting appears in many DevOps, SRE, and Linux admin job descriptions and remains a standard shell on Unix-like systems; no vendor sunset or clear replacement has displaced it.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
98
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages for ML Systems
programming-languages-for-ml-systems
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
CP4D Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

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)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
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
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Unix shell scripting new
Programming Languages for ML Systems
programming-languages-for-ml-systems
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Datastage | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed CP4D | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
dimension_skill_link_proposed Unix shell scripting ↔ Programming Languages for ML Systems
nano JD Parser — gpt-4.1-nano click to toggle
Experience6+ years of experience
DomainIT Services & Consulting
Location Hyderabad, India (null)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "ai_kras": [],
  "certifications": [],
  "client_details": null,
  "company_name": null,
  "company_size": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC - Any Discipline",
      "raw": "Graduation score should be 60% \u0026 above",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 6,
    "raw": "6+ years of experience"
  },
  "job_locations": [
    {
      "aliases": [],
      "city": "Hyderabad",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [],
      "city": "Pune",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [],
      "city": "Chennai",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [
        "Bengaluru"
      ],
      "city": "Bangalore",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [
        "Thiruvananthapuram"
      ],
      "city": "Trivandrum",
      "country": "India",
      "state": null,
      "work_mode": "null"
    }
  ],
  "notice_period": {
    "days": 30,
    "raw": "Immediate to 15-30 days ONLY."
  },
  "open_to_relocate": false,
  "role": null,
  "role_aliases": [],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Must have skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Must have skills -CP4D, Unix",
        "last_5_words": "scripting , Datastage , SQL"
      },
      "text": "CP4D, Unix shell scripting , Datastage , SQL",
      "word_count": 8
    },
    {
      "bullet_count": 14,
      "heading": "Significant",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "- At least 6+ years of",
        "last_5_words": "new technologies and industry trends in Development."
      },
      "text": "- At least 6+ years of experience in designing and developing large scale, distributed data processing pipelines using Datastage related technologies.\n- Having expertise in Datastage ETL Batch processing\n- Expericence with Data warehousing and ETL concepts and techniques\n- UNIX shell scripting will be an added advantage in scheduling/running application jobs.\n- Experience with cloud pak for data will be added advantage\n- At least 5 years of experience in Project development life cycle activities and development/maintenance projects\n- Work with business stakeholders and other SMEs to understand high level business requirements.\n- Work with the Solution Designers and contribute to the development of project plans by participating in the scoping and estimating of proposed project.\n- Apply technical background understanding, business knowledge, system knowledge in the elicitation of Systems Requirements for projects.\n- Work in an Agile environment and participation in scrum daily standups, sprint planning reviews and retrospectives.\n- Understand project requirements and translate them into technical solutions which meets the project quality standards\n- Ability to work in team in diverse/multiple stakeholder environment and collaborate with upstream/downstream functional teams to identify, troubleshoot and resolve data issues.\n- Strong problem solving and Positive Analytical skills.\n- Excellent verbal and written communication skills.\n- Experience and desire to work in a Global delivery environment.\n- Stay up to date with new technologies and industry trends in Development.",
      "word_count": 284
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "dimension": null,
      "is_primary": true,
      "layer": "L2",
      "layer_source": "llm",
      "rationale": "Datastage is mentioned in the context of responsibilities, indicating its importance in the role.",
      "skill_name": "Datastage"
    },
    {
      "dimension": {
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "slug": "programming-languages-for-data-work"
      },
      "is_primary": true,
      "layer": "L0",
      "layer_source": "baseline",
      "rationale": "Anchor dimension: Programming Languages for Data Work",
      "skill_name": "SQL"
    },
    {
      "dimension": null,
      "is_primary": false,
      "layer": null,
      "layer_source": null,
      "rationale": null,
      "skill_name": "Unix shell scripting"
    },
    {
      "dimension": null,
      "is_primary": false,
      "layer": null,
      "layer_source": null,
      "rationale": null,
      "skill_name": "CP4D"
    },
    {
      "dimension": null,
      "is_primary": true,
      "layer": "L2",
      "layer_source": "baseline",
      "rationale": "Agile is already at baseline L2 and is supported by evidence of participation in Agile practices.",
      "skill_name": "Agile"
    }
  ],
  "jd_parameters": {
    "certifications": [],
    "clientDetails": null,
    "company": null,
    "companySize": null,
    "ctc": {
      "currency": null,
      "max": null,
      "min": null,
      "period": null,
      "raw": null
    },
    "educationRequirements": [
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    "experience": {
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      "min": 6,
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    "industryDomain": "IT Services \u0026 Consulting",
    "knockouts": {
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      "ctc": {
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      },
      "educationRequirements": [
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      "location": [
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    "locations": [
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    "noticePeriod": 30,
    "openToRelocate": false,
    "role": null,
    "roleSynonyms": []
  },
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "ai_kras": [],
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        "aliases": [],
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        "aliases": [
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    ],
    "notice_period": {
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    },
    "open_to_relocate": false,
    "role": null,
    "role_aliases": [],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Must have skills",
        "heading_was_present": true,
        "source_marker": {
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  "rejection_reason": null,
  "role": {
    "anchor_type": null,
    "dimensions": [
      {
        "bimodal": false,
        "default_layer": "L0",
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "slug": "programming-languages-for-data-work"
      },
      {
        "bimodal": false,
        "default_layer": "L1",
        "display_name": "Cloud Data Warehouses",
        "id": 22,
        "slug": "cloud-data-warehouses"
      },
      {
        "bimodal": false,
        "default_layer": "L1",
        "display_name": "Data Pipeline Orchestration",
        "id": 23,
        "slug": "data-pipeline-orchestration"
      },
      {
        "bimodal": false,
        "default_layer": "L0",
        "display_name": "ETL and ELT Tooling",
        "id": 24,
        "slug": "etl-and-elt-tooling"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Cloud Platforms",
        "id": 20,
        "slug": "cloud-platforms"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Stream Processing Systems",
        "id": 25,
        "slug": "stream-processing-systems"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Modeling and Schema Design",
        "id": 26,
        "slug": "data-modeling-and-schema-design"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Quality and Reconciliation",
        "id": 27,
        "slug": "data-quality-and-reconciliation"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Lineage and Metadata",
        "id": 28,
        "slug": "data-lineage-and-metadata"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Batch Ingestion and Replication",
        "id": 29,
        "slug": "batch-ingestion-and-replication"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Messaging and Event Streaming",
        "id": 8,
        "slug": "messaging-and-event-streaming"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "BI and Visualization Tools",
        "id": 31,
        "slug": "bi-and-visualization-tools"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Governance and Access Controls",
        "id": 32,
        "slug": "data-governance-and-access-controls"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
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        "slug": "performance-and-cost-optimization"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Recovery and Backfill Operations",
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        "slug": "data-recovery-and-backfill-operations"
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      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Cloud Storage and File Formats",
        "id": 35,
        "slug": "cloud-storage-and-file-formats"
      },
      {
        "bimodal": false,
        "default_layer": "L2",
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        "slug": "data-contracts-and-delivery-slas"
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      {
        "bimodal": false,
        "default_layer": "L2",
        "display_name": "Data Serialization Standards \u0026 Protocols",
        "id": 37,
        "slug": "data-serialization-standards-protocols"
      }
    ],
    "display_name": "Data Engineer",
    "id": 2,
    "resolution": "in_db",
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  "run_id": "7966f25e-ddd5-4924-bc17-1dd016791994",
  "secondary_skills": [
    "Unix shell scripting",
    "CP4D"
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  "skill_layers": [
    {
      "label": "Anchor",
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      "skills": [
        {
          "dimension": {
            "display_name": "Programming Languages for Data Work",
            "id": 21,
            "slug": "programming-languages-for-data-work"
          },
          "name": "SQL",
          "rationale": "Anchor dimension: Programming Languages for Data Work"
        }
      ]
    },
    {
      "label": "Environment",
      "layer": "L2",
      "skills": [
        {
          "name": "Datastage",
          "rationale": "Datastage is mentioned in the context of responsibilities, indicating its importance in the role."
        },
        {
          "name": "Agile",
          "rationale": "Agile is already at baseline L2 and is supported by evidence of participation in Agile practices."
        }
      ]
    }
  ],
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
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      {
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          },
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        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
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        "total_count": null
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": [
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            "kra_text": "Requirements analysis and process translation",
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            "kra_text": "Requirements analysis and process translation",
            "sentence": "Apply technical background understanding, business knowledge, system knowledge in the elicitation of Systems Requirements for projects.",
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          },
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        "matched_count": null,
        "matched_skills": null,
        "role_id": 24,
        "score": 0.5273,
        "slug": "pega-developer",
        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
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            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
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          },
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          }
        ],
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        "matched_skills": null,
        "role_id": 15,
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        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
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            "sentence": "Understand project requirements and translate them into technical solutions which meets the project quality standards",
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          },
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            "kra_text": "collaborate with design, product, and backend teams",
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          },
          {
            "kra_text": "collaborate with design, product, and backend teams",
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        ],
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        "total_count": null
      },
      {
        "display_name": "ML Engineer",
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        ],
        "matched_count": null,
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      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Engineering Manager",
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        "matched_count": 2,
        "matched_skills": [
          "Agile",
          "SQL"
        ],
        "role_id": 121,
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        "slug": "engineering-manager",
        "total_count": 3
      },
      {
        "display_name": "Fullstack Developer",
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          "SQL"
        ],
        "role_id": 15,
        "score": 0.3333,
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        "total_count": 3
      },
      {
        "display_name": "Data Engineer",
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          "SQL"
        ],
        "role_id": 2,
        "score": 0.3333,
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        "total_count": 3
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
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          "SQL"
        ],
        "role_id": 1,
        "score": 0.3333,
        "slug": "backend-engineer",
        "total_count": 3
      },
      {
        "display_name": "WordPress Dev",
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        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 227,
        "score": 0.3333,
        "slug": "wordpress-dev",
        "total_count": 3
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "D",
    "chosen_role": {
      "display_name": "Data Engineer",
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      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.5392,
      "slug": "data-engineer",
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    },
    "confidence": 0.87,
    "consensus_evidence": {},
    "is_new_role": false,
    "llm2_fired": true,
    "llm2_reasoning": "The JD focuses on hands-on ETL pipeline development, Datastage, SQL and data warehousing which aligns with a Data Engineer role rather than an Engineering Manager.",
    "matched_dimensions": [],
    "matched_kras": [],
    "matched_skills": [],
    "new_role_display_name": null,
    "new_role_domain": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "LLM2 picked data-engineer (confidence 0.87)",
    "role_aliases": [],
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 529,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 26307,
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        "skill_name": "Datastage",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 26308,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Unix shell scripting",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 26309,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "CP4D",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
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      "input_term": "SQL",
      "matched_canonical": {
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        "display_name": "SQL",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 429,
      "existing_alias_text": "Bash scripting",
      "input_term": "Unix shell scripting",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
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        "sub_category_id": 98,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 868,
      "existing_alias_text": "Agile",
      "input_term": "Agile",
      "matched_canonical": {
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        "display_name": "Agile",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
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      "slug": "pega-developer",
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    },
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      "slug": "ml-ops-engineer",
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  "chosen_role": {
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    "rationale": "LLM2 picked data-engineer (confidence 0.87)",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages",
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        "slug": "programming-languages",
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      },
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      ]
    },
    {
      "dimension": {
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        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
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    },
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    },
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    },
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      },
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      "roles_from_db": []
    },
    {
      "dimension": {
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      },
      "source_tag": "llm",
      "was_in_llm_skills": true
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      ],
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              "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"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 435,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "fullstack-developer",
              "source": "db"
            },
            {
              "display_name": "WordPress Dev",
              "id": 227,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "wordpress-dev",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages \u0026 DSLs",
            "id": 475,
            "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
            "slug": "programming-languages-dsls",
            "source": "db"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        },
        {
          "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"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "SQL",
      "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": "Bash scripting",
          "alias_type": "CANONICAL",
          "id": 429,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 6,
        "display_name": "Bash scripting",
        "id": 193,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "bash-scripting",
        "sub_category_id": 98,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "Unix shell scripting",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Unix shell scripting",
      "matched_via": "embedding_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": [],
      "input_skill": "CP4D",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "cp4d",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Agile",
          "alias_type": "CANONICAL",
          "id": 868,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Agile",
        "id": 520,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "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": "Agile",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Software Concepts, Patterns \u0026 Practices",
            "id": 478,
            "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
            "slug": "software-concepts-patterns-practices",
            "source": "db"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Agile",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Datastage",
    "CP4D"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "LLM2 picked data-engineer (confidence 0.87)",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Datastage",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Unix shell scripting",
      "tag": "in_db"
    },
    {
      "skill": "CP4D",
      "tag": "new"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "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": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Core programming languages and markup used in WordPress development.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "SQL",
        "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 Developer",
            "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"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          },
          {
            "display_name": "WordPress Dev",
            "id": 227,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "wordpress-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "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": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "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": "SQL",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "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": "Unix shell scripting",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "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": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Software Concepts, Patterns \u0026 Practices",
          "id": 478,
          "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
          "slug": "software-concepts-patterns-practices",
          "source": "db"
        },
        "dimension_id": 478,
        "input_skill": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 1
  },
  "planner_output": null,
  "run_id": "7966f25e-ddd5-4924-bc17-1dd016791994"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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