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Rafid CV-Job Match Scorer
x402
Rafid CV-Job Match Scorer is a paid API for AI agents from api.rafidsystem.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-10-10).
Scores how well a candidate's CV matches a job description, returning a structured match score, skill analysis, gap analysis, and hiring decision support.
Price / call$0.25
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: an overall match_score (0-100), a confidence value, category_scores broken down by domain, education, experience, certifications, required_skills, and responsibilities, a skill_match array with per-requirement status and evidence, a decision_support object listing strong matches, partial matches, and missing required/preferred skills, an experience_analysis with required vs candidate years, a list of gaps, risk_flags, transferable_skills, and a plain-language explanation.
Example use cases
ATS shortlisting for engineering role
“I have 50 applicants for a senior Python engineer role. Can you score this candidate's CV against the job description and tell me the overall match score, which required skills they have, and what's missing so I can decide if they should advance?”
Career advisor gap analysis
“My client wants to apply for a data analyst position but I'm not sure they're ready. Can you compare their CV to this job description and show me the skill gaps, missing certifications, and how many years of experience they still need?”
Self-assessment before applying
“I'm thinking of applying to this product manager role — can you match my CV against the job description and give me a score with a breakdown of where I'm strong, where I'm weak, and what skills I should highlight or develop?”
Technical details
Endpoint
POSThttps://api.rafidsystem.com/api/v1/x402/recruitment/cv-job-match?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a structured, quantitative match score between a specific CV and a specific job description — especially when you need per-skill breakdown, experience gap analysis, and decision-support output rather than a simple pass/fail. Prefer this over general LLM summarization when you need consistent scoring categories and machine-readable results for downstream ranking or filtering workflows.
Side effects
- CV text or job description not provided — returns validation error
- CV or job description exceeds character limits (200k/100k) — truncation or rejection
- Poorly structured or empty input text yields low-confidence scores
- Ambiguous skill names may result in unmatched requirements despite candidate having them
- Non-English CVs or job descriptions may reduce accuracy
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| cv_text | string | |
| job_profile | — | |
| job_description | string | |
| candidate_profile | — |
Output
Schema · Response
{
"type": "json",
"example": {
"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": [
{
"status": "matched",
"confidence": 0.9,
"requirement": "Python",
"candidate_evidence": "Python"
}
],
"category_scores": {
"domain": 50,
"education": 50,
"experience": 100,
"certifications": 50,
"required_skills": 100,
"responsibilities": 50
},
"decision_support": {
"strong_match": [
"Python",
"SQL"
],
"partial_match": [],
"missing_required": [],
"missing_preferred": []
},
"experience_analysis": {
"required_years": 3,
"candidate_years": 5
},
"transferable_skills": []
}
}Tags
x402
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