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Rafid Recruitment Candidate Shortlist Scorer
x402
Rafid Recruitment Candidate Shortlist Scorer is a paid API for AI agents from api.rafidsystem.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-11).
Scores and ranks a list of candidates against a job profile, returning match scores, skill gaps, risk flags, and decision-support explanations for each candidate.
Price / call$0.1
Success—
StatusUnknown
How this service works
Rafid Agent API provides structured intelligence and paid APIs for AI agents across property, company and risk, supplier, finance, document, website, automotive, logistics, recruitment, trading, voice, video and business-planning workflows.
Output
Returns a JSON object containing the parsed job requirements (required skills, experience years), a ranked array of candidates each with: match_score (0-100), skill_match list, gaps, transferable_skills, experience_analysis, risk_flags, confidence (0-1), explanation text, category_scores, and decision_support fields, plus a scoring_methodology block detailing weights and a statement that protected attributes are never used.
Example use cases
Automated applicant screening pipeline
“I have 40 applicants for our Data Analyst role requiring SQL and Tableau skills with at least 2 years of experience — can you score all of them against the job profile and return the top 10 with match scores and skill gap analysis?”
Comparing finalists before interview stage
“We've narrowed it down to 6 candidates for the Marketing Manager position — can you score each of them against our job profile and show me their match scores, any risk flags, and which transferable skills they bring?”
Bias-free shortlisting for compliance
“We need to shortlist 5 candidates from this pool of 20 for our Software QA role in a way that ignores protected attributes — can you run them all through the candidate scoring system and return a ranked list with confidence scores and explanations for each score?”
Technical details
Endpoint
POSThttps://api.rafidsystem.com/api/v1/x402/recruitment/candidate-shortlist-score?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need structured, explainable AI-driven candidate scoring against a defined job profile — especially when you require skill gap identification, risk flagging, experience analysis, and a bias-disclosure (protected attributes ignored) audit trail. Prefer this over generic LLM prompting when you need consistent numeric match scores and methodology transparency for compliance or HR reporting purposes.
Side effects
- Empty or malformed candidate_profile objects result in low-confidence or error responses
- Exceeding 100 candidates in the array returns a validation error
- Missing job_profile causes scoring to be underdetermined or absent
- Vague or under-specified candidate profiles produce low confidence scores
- Payment failure (x402) results in 402 response before processing begins
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| candidates | array | |
| job_profile | object | |
| max_candidates | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"job": {
"required_skills": [
{
"skill": "Python"
}
],
"required_experience_years": 2
},
"candidates": [
{
"gaps": [],
"confidence": 0.7,
"risk_flags": [],
"explanation": "Score is based on normalized job-relevant skills and supplied experience evidence only.",
"match_score": 80,
"skill_match": [],
"candidate_id": "CAND-001",
"category_scores": {},
"decision_support": {},
"experience_analysis": {},
"transferable_skills": []
}
],
"scoring_methodology": {
"weights": {
"evidence": 20,
"experience": 30,
"required_skills": 50
},
"protected_attributes": "Ignored; never used for scoring or ranking."
}
}
}Tags
x402
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