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Pipeline run

afea12af-2bee-4396-acd0-a1471adb96a0

Pipeline LLM cost (USD)

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

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: 2026-05-27T14:13:25.056878Z Updated: 2026-05-27T14:13:25.056878Z

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 responsible for delivering a good,reliable and logical code for the given module. An initial training will be provided for less/no experience candidate


Responsibilities


Candidate must put a good quality of the research on the given module or problem statement
Candidate must provide logical, reliable and error free solutions.
Candidate must follow the process and on time quality of code delivery.


Qualifications


Any Bachelor's/Master's degree in any field
Candidates with CS background will be appreciated
Good analytical skills
Understanding of his/her area of expertise

Library artifacts (this run)

No artifact rows for this run.

API 1 — extract-from-jd click to toggle

{
  "final_skills": [],
  "jd_role": {
    "display_name": "The ideal candidate will be responsible for delivering a good,reliable and logical code for the given module. An initial training will be provided for less/no experience candidate",
    "rationale": "JD body too sparse: 61 words, 0 tech-marker hits \u2014 needs more detail (\u003e=80 words or \u003e=2 tech markers) for confident classification",
    "role_aliases": [],
    "role_archetype": "Other",
    "slug": ""
  },
  "nano_parsed": null,
  "rejected": true,
  "rejection_reason": "Sparse JD: JD body too sparse: 61 words, 0 tech-marker hits \u2014 needs more detail (\u003e=80 words or \u003e=2 tech markers) for confident classification",
  "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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