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Pipeline run

56e5af59-6725-46eb-a8e8-9cfc32e098f4

Pipeline LLM cost (USD)
API 1: $0.0111 API 2: $0.0005 API 3: $0.0000 Total: $0.0116

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · APM support and administration
Supports APM/Meridium by handling upgrades, policy/instance validation, bulk TML analysis, data loads from Maximo, SSRS reporting, SQL-based data checks, user onboarding, and day-to-day troubleshooting/change requests.
""Taking care of the support activities and raising the tickets for the same in client ticketing tool.""
Tech stack maturity
Mainstream Modern
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 (7)
SQL SSRS Maximo Meridium APM APM Connect Administration Center UAT
Skill cluster (2 dimension groups, role-scoped)
Pega Programming Languages & DSLs
SQL
Cross-cutting / unaligned
SSRS Maximo Meridium APM APM Connect Administration Center UAT
Show KRA description ↓
Experience in APM_GE Support Analyst for APM 4.3 version. • Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest. • Designing and execution of policy in the Meridium and analyzing Instance validation and execution. • Running Bulk analysis on the TMLs on frequent basis. • Designing of SSRS reports and deploying them into APM. • Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any. • Also working on health indicators and PI Tags. • Good understanding of APM Connect Administration center. • Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend. • Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups. • Configuration and troubleshooting Meridium instances with various modules. • Interacting with the business users, collecting requirements, and providing solutions. • Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide. • Taking care of the support activities and raising the tickets for the same in client ticketing tool. • Raising change requests and implementing change in the application. • Experience on enhancement tasks to make the Customization and Development. • Experience on policy designer Creating SQL queries based on client request and for SSRS report

Signals

Skill data-engineer
0.14
Alias
KRA full-stack-engineer
0.50

Post-classification

Centroid
Alias collision log
New-role queue#58
New skills captured0
New KRA captured
Status: completed Created: 2026-05-27T13:42:47.161230Z Updated: 2026-05-27T13:45:13.894155Z API 3 duration: 13391 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

Pega Developer

CASE F

slug: pega-developer · id: 24 · source: db

The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.

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
0
Skipped

Job description

A technology services client of ours is looking for multiple APM_GE Support Analysts to join them on a Contract basis.


Job Title : APM_GE Support Analyst
Experience Needed: 5 - 8 years
Location: Mumbai/Pune/Chennai/Bangalore/Hyderabad/Delhi/Noida/Kolkata,
Notice Period: Immediate Joiners
Required Skills: APM 4.3 version to APM 5 Version, SSRS reports,TMLs APM connect
Payroll: Swift Staffing solutions
Client: LTIMindtree


JR Number : 1259182
Role Description:
Experience in APM_GE Support Analyst for APM 4.3 version.
• Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest.
• Designing and execution of policy in the Meridium and analyzing Instance validation and execution.
• Running Bulk analysis on the TMLs on frequent basis.
• Designing of SSRS reports and deploying them into APM.
• Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.
• Also working on health indicators and PI Tags.
• Good understanding of APM Connect Administration center.
• Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.
• Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups.
• Configuration and troubleshooting Meridium instances with various modules.
• Interacting with the business users, collecting requirements, and providing solutions.
• Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.
• Taking care of the support activities and raising the tickets for the same in client ticketing tool.
• Raising change requests and implementing change in the application.
• Experience on enhancement tasks to make the Customization and Development.
• Experience on policy designer Creating SQL queries based on client request and for SSRS report


Feel free to reach out to safa.m@s3staff.com for any additional information.

Skills from this JD

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

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
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

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 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 saved
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SSRS 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
Reporting Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Maximo 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
Asset Management Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Meridium 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
Asset Management Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
APM 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
Application Performance Monitoring
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
APM Connect Administration Center 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
Application Performance Monitoring
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
UAT 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
Testing Processes
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

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 saved
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed SSRS | type=Reporting Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Maximo | type=Asset Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Meridium | type=Asset Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed APM | type=Application Performance Monitoring subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed APM Connect Administration Center | type=Application Performance Monitoring subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed UAT | type=Testing Processes subtype=general nature=PRACTICE lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleAPM_GE Support Analyst
CompanyLTIMindtree
Experience5 - 8 years
DomainIT Services & Consulting
Location Mumbai, India
JD type pass
Show raw JSON
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  "certifications": [],
  "company_name": "LTIMindtree",
  "ctc": null,
  "domain": {
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  "education": [],
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  "job_locations": [
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      "state": null,
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    },
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      "aliases": [],
      "city": "Pune",
      "country": "India",
      "state": null,
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    },
    {
      "aliases": [
        "Madras"
      ],
      "city": "Chennai",
      "country": "India",
      "state": null,
      "work_mode": null
    },
    {
      "aliases": [
        "Bengaluru"
      ],
      "city": "Bangalore",
      "country": "India",
      "state": "Karnataka",
      "work_mode": null
    },
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      "aliases": [],
      "city": "Hyderabad",
      "country": "India",
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      "aliases": [],
      "city": "Delhi",
      "country": "India",
      "state": null,
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    },
    {
      "aliases": [],
      "city": "Noida",
      "country": "India",
      "state": null,
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    },
    {
      "aliases": [
        "Calcutta"
      ],
      "city": "Kolkata",
      "country": "India",
      "state": null,
      "work_mode": null
    }
  ],
  "role": "APM_GE Support Analyst",
  "role_aliases": [
    "Support Analyst",
    "APM Support Analyst"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
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      "bullet_count": 15,
      "heading": "Role Description",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Experience in APM_GE Support Analyst",
        "last_5_words": "and for SSRS report"
      },
      "text": "Experience in APM_GE Support Analyst for APM 4.3 version.\n\u2022 Should have experience on APM_GE Upgradation from APM 4.3 version to APM 5 Version or latest.\n\u2022 Designing and execution of policy in the Meridium and analyzing Instance validation and execution.\n\u2022 Running Bulk analysis on the TMLs on frequent basis.\n\u2022 Designing of SSRS reports and deploying them into APM.\n\u2022 Good knowledge of Data load interface enabling bulk data load from Maximo to Meridium by syncing Functional locations, equipment. Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.\n\u2022 Also working on health indicators and PI Tags.\n\u2022 Good understanding of APM Connect Administration center.\n\u2022 Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.\n\u2022 Onboarding new users into APM and giving proper privileges and assigning relevant roles and groups.\n\u2022 Configuration and troubleshooting Meridium instances with various modules.\n\u2022 Interacting with the business users, collecting requirements, and providing solutions.\n\u2022 Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.\n\u2022 Taking care of the support activities and raising the tickets for the same in client ticketing tool.\n\u2022 Raising change requests and implementing change in the application.\n\u2022 Experience on enhancement tasks to make the Customization and Development.\n\u2022 Experience on policy designer Creating SQL queries based on client request and for SSRS report",
      "word_count": 309
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  ],
  "urls": [
    {
      "type": "other",
      "url": "mailto:safa.m@s3staff.com"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "SSRS"
    },
    {
      "is_primary": true,
      "skill_name": "Maximo"
    },
    {
      "is_primary": true,
      "skill_name": "Meridium"
    },
    {
      "is_primary": true,
      "skill_name": "APM"
    },
    {
      "is_primary": true,
      "skill_name": "APM Connect Administration Center"
    },
    {
      "is_primary": true,
      "skill_name": "UAT"
    }
  ],
  "jd_role": {
    "display_name": "APM_GE Support Analyst",
    "rationale": null,
    "role_aliases": [
      "Support Analyst",
      "APM Support Analyst"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
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      "Make",
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    ],
    "certifications": [],
    "company_name": "LTIMindtree",
    "ctc": null,
    "domain": {
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        "aliases": [
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        ],
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      },
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    },
    "education": [],
    "experience": {
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      "min": 5,
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    "job_locations": [
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        ],
        "city": "Mumbai",
        "country": "India",
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      },
      {
        "aliases": [],
        "city": "Pune",
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        ],
        "city": "Chennai",
        "country": "India",
        "state": null,
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      },
      {
        "aliases": [
          "Bengaluru"
        ],
        "city": "Bangalore",
        "country": "India",
        "state": "Karnataka",
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      },
      {
        "aliases": [],
        "city": "Hyderabad",
        "country": "India",
        "state": null,
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      },
      {
        "aliases": [],
        "city": "Delhi",
        "country": "India",
        "state": null,
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      },
      {
        "aliases": [],
        "city": "Noida",
        "country": "India",
        "state": null,
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      },
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        "aliases": [
          "Calcutta"
        ],
        "city": "Kolkata",
        "country": "India",
        "state": null,
        "work_mode": null
      }
    ],
    "role": "APM_GE Support Analyst",
    "role_aliases": [
      "Support Analyst",
      "APM Support Analyst"
    ],
    "role_archetype": "Engineering",
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        "bullet_count": 15,
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  "rejected": false,
  "rejection_reason": null,
  "run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
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        "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.",
            "sentence": "Interacting with the business users, collecting requirements, and providing solutions.",
            "similarity": 0.5618
          },
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
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            "similarity": 0.5084
          },
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
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            "sentence": "Interacting with the business users, collecting requirements, and providing solutions.",
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          },
          {
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            "sentence": "Writing SQL queries to perform data analysis and data extraction as per the requirement both in front end and backend.",
            "similarity": 0.4932
          },
          {
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          }
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        "role_id": 2,
        "score": 0.4903,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Drupal Dev",
        "kra_matches": [
          {
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            "similarity": 0.5552
          },
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            "similarity": 0.4544
          },
          {
            "kra_text": "site troubleshooting and defect fixes",
            "sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
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          }
        ],
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        "matched_skills": null,
        "role_id": 228,
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        "slug": "drupal-dev",
        "total_count": null
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": [
          {
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            "sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
            "similarity": 0.4715
          },
          {
            "kra_text": "Supports ML platform incidents by diagnosing model serving failures, feature store pipeline breaks, and training environment configuration issues.",
            "sentence": "Also manually loading TML, Health indictors, OPC Tags, Log categories and different data into APM and analyzing the errors and correcting if any.",
            "similarity": 0.4574
          },
          {
            "kra_text": "Coordinates model promotion workflows across development, staging, and production environments including integration testing and data contract validation.",
            "sentence": "Experience on enhancement tasks to make the Customization and Development.",
            "similarity": 0.4556
          }
        ],
        "matched_count": null,
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        "role_id": 16,
        "score": 0.4615,
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        "total_count": null
      },
      {
        "display_name": "Cyber Security Engineer",
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            "similarity": 0.4879
          },
          {
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            "sentence": "Designing and execution of policy in the Meridium and analyzing Instance validation and execution.",
            "similarity": 0.4614
          },
          {
            "kra_text": "Conducts security posture assessments, vulnerability scans, and penetration testing to identify weaknesses and evaluate overall system security.",
            "sentence": "Preforming UAT testing and preparing Test scripts, training documents, APM framework user guide.",
            "similarity": 0.434
          }
        ],
        "matched_count": null,
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    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
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          "SQL"
        ],
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      },
      {
        "display_name": "Pega Developer",
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        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 24,
        "score": 0.1429,
        "slug": "pega-developer",
        "total_count": 7
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "F",
    "chosen_role": null,
    "confidence": 0.65,
    "is_new_role": false,
    "llm2_fired": true,
    "llm2_reasoning": "The JD\u2019s focus on SQL-based data integration, ETL processes, SSRS reporting and data analysis aligns closely with a Data Engineer role.",
    "matched_dimensions": [],
    "matched_kras": [],
    "matched_skills": [],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": true,
    "reasoning": "LLM2 unsure (confidence 0.65 \u003c 0.7); queueing",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": null,
    "centroid_updated": false,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [],
    "queue_entry_id": 58,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
      "existing_alias_text": "SQL",
      "input_term": "SQL",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "SQL",
        "id": 101,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Pega Developer",
    "id": 24,
    "rationale": "The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.",
    "role_archetype": null,
    "slug": "pega-developer",
    "source": "db"
  },
  "dimensions": [
    {
      "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"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "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_final_skills": [
    "SQL",
    "SSRS",
    "Maximo",
    "Meridium",
    "APM",
    "APM Connect Administration Center",
    "UAT"
  ],
  "input_llm_skills": [
    "SQL",
    "SSRS",
    "Maximo",
    "Meridium",
    "APM",
    "APM Connect Administration Center",
    "UAT"
  ],
  "new_aliases_persisted": 0,
  "run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4",
  "skills_detail": [
    {
      "aliases_in_db": [
        {
          "alias_text": "SQL",
          "alias_type": "CANONICAL",
          "id": 271,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 6,
        "display_name": "SQL",
        "id": 101,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Pega Developer",
              "id": 24,
              "rationale": null,
              "role_archetype": null,
              "slug": "pega-developer",
              "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": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "SSRS",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Reporting Tools",
          "skill_nature": "TOOL",
          "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": "ssrs",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Maximo",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Asset Management Tools",
          "skill_nature": "TOOL",
          "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": "maximo",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Meridium",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Asset Management Tools",
          "skill_nature": "TOOL",
          "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": "meridium",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "APM",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Application Performance Monitoring",
          "skill_nature": "CONCEPT",
          "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": "apm",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "APM Connect Administration Center",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Application Performance Monitoring",
          "skill_nature": "TOOL",
          "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": "apm-connect-administration-center",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "UAT",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Testing Processes",
          "skill_nature": "PRACTICE",
          "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": "uat",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "SSRS",
    "Maximo",
    "Meridium",
    "APM",
    "APM Connect Administration Center",
    "UAT"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Pega Developer",
    "id": 24,
    "rationale": "The primary skills align closely with the Pega Developer role, particularly with SQL and other related technologies.",
    "role_archetype": null,
    "slug": "pega-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "SSRS",
      "tag": "new"
    },
    {
      "skill": "Maximo",
      "tag": "new"
    },
    {
      "skill": "Meridium",
      "tag": "new"
    },
    {
      "skill": "APM",
      "tag": "new"
    },
    {
      "skill": "APM Connect Administration Center",
      "tag": "new"
    },
    {
      "skill": "UAT",
      "tag": "new"
    }
  ],
  "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": 24,
        "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": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "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": 24,
        "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": 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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "56e5af59-6725-46eb-a8e8-9cfc32e098f4"
}

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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