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Pipeline run

19819a58-f1a1-46c9-b49b-0b2913139f24

Pipeline LLM cost (USD)

API 1: $0.0017 API 2: $0.0000 API 3: $0.0000 Total: $0.0017

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: extract_from_jd_done Created: 2026-05-27T14:00:37.552575Z Updated: 2026-05-27T14:00:37.552575Z

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

No chosen role stored for this run.

Job description

The ideal candidate will be familiar with the full software design life cycle. They should have experience in designing, coding, testing and consistently managing applications They should be comfortable coding in a number of languages and have an ability to test code in order to maintain high-quality code.    Responsibilities Design, code, test and manage various applications Collaborate with engineering team and product team to establish best products Follow outlined standards of quality related to code and systems Develop automated tests and conduct performance tuning Qualifications Bachelor's degree in Computer Science or relevant field 1 to 2 years of experience working with .NET or relevant experiences Experience developing web-based applications in C#, HTML, JavaScript, VBScript/ASP, or .NET

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); body has only 0 canonical-skill mentions and 0 tech-marker hits \u2014 insufficient evidence",
    "role_aliases": [],
    "role_archetype": "\u2014",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "fail"
  },
  "rejected": true,
  "rejection_reason": "Stage 1 marked JD_type=fail (unparseable); body has only 0 canonical-skill mentions and 0 tech-marker hits \u2014 insufficient evidence",
  "run_id": null,
  "stage3_signals": null,
  "stage4_decision": null,
  "stage5_updates": null
}

API 2 — extract-details

{}

API 3 — final-role-output

{}

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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