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Pipeline run

88c86538-4ef4-469a-8952-fbed8bd1a5ce

Pipeline LLM cost (USD)

API 1: $0.0016 API 2: $0.0000 API 3: $0.0000 Total: $0.0016

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

SPARSE JD

Nature of work

—

no_db_connection

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 (0)

No skills extracted

Skill cluster (0 dimension groups, role-scoped)

No dimension groups computed for this JD.

Status: completed Created: 2026-05-20T21:52:01.804282Z Updated: 2026-05-20T21:52:01.867994Z API 3 duration: 26 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

—

slug: — · id: — · source: llm

Stage 1 marked JD_type=fail (unparseable)

Resolution: human_review_required — role not in DB; role↔dimension links may be deferred.

New skills

Skill↔dim saved

Role↔dim saved

Skipped

Job description

• 5+ years of Middleware/Integration experience (any platform) with at least 3 full life cycle MuleSoft Project experience (Analysis, Design, Dev, Testing, Deployment)
• Good understanding of MuleSoft Deployment/Physical architecture (On Prem, on Cloud and Hybrid)
• Expertise in message transformation, validation, routing, and orchestration in MuleSoft
• Ability to define MuleSoft design and development best practices and testing guides etc.
• Experience in API Management on MuleSoft platform
• Ability to design and develop enterprise services using RAML in Mule, REST-based APIs, SOAP Web Services, and the use of different mule connectors.
• Experience in Software Engineering Lifecycle Management using Agile methodology.
• Understanding of MuleSoft DevOps support and capabilities.
• Experience in managing and deploying MuleSoft applications.
• Ability to lead a team of onsite and offshore developers.
• Familiarity with Salesforce workbench, orgs, objects, and properties
• A basic understanding of API-led connectivity, API reuse, and Salesforce integration patterns.
• In depth knowledge on salesforce connector like upsert, create, query query single
• Good to have MuleSoft Developer certification and advance level certifications.

Library artifacts (this run)

No artifact rows for this run.

nano JD Parser — gpt-4.1-nano click to toggle

JD type fail

Show raw JSON

{
  "JD_type": "fail"
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [],
  "jd_role": {
    "display_name": "\u2014",
    "rationale": "Stage 1 marked JD_type=fail (unparseable)",
    "role_aliases": [],
    "role_archetype": "\u2014",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "fail"
  },
  "rejected": true,
  "rejection_reason": "Stage 1 marked JD_type=fail (unparseable)",
  "run_id": null,
  "stage3_signals": null,
  "stage4_decision": null,
  "stage5_updates": null
}

API 2 — extract-details

{
  "alias_matches": [],
  "candidate_roles": [],
  "chosen_role": {
    "display_name": "\u2014",
    "id": null,
    "rationale": "Stage 1 marked JD_type=fail (unparseable)",
    "role_archetype": "\u2014",
    "slug": "",
    "source": "llm"
  },
  "dimensions": [],
  "input_final_skills": [],
  "input_llm_skills": [],
  "new_aliases_persisted": 0,
  "run_id": "88c86538-4ef4-469a-8952-fbed8bd1a5ce",
  "skills_detail": [],
  "unmatched_skills": []
}

API 3 — final-role-output

{
  "chosen_role": {
    "display_name": "\u2014",
    "id": null,
    "rationale": "Stage 1 marked JD_type=fail (unparseable)",
    "role_archetype": "\u2014",
    "slug": "",
    "source": "llm"
  },
  "chosen_role_resolution": "human_review_required",
  "final_input_skills": [],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "88c86538-4ef4-469a-8952-fbed8bd1a5ce"
}

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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