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Skill Gap Analyzer
x402
Skill Gap Analyzer is a paid API for AI agents from api.strale.io, paid per call via x402, $0.162/call, status unknown (last checked 2026-10-12).
Compares required skills against candidate skills using fuzzy matching and returns matched, missing, extra skills, and an overall match score.
Price / call$0.162
Success—
StatusUnknown
How this service works
Compare required skills against candidate skills with fuzzy matching. Returns matched, missing, extra, and match score.
Output
Returns a structured breakdown of matched skills (with fuzzy matches), missing skills the candidate lacks, extra skills the candidate has beyond requirements, and a numeric match score indicating overall fit percentage.
Example use cases
Resume screening for engineering openings
“Check how well this candidate's resume matches our senior backend engineer requirements. We need Java, Kubernetes, microservices architecture, and AWS — can you tell me what they have, what they're missing, and give me a match score so we can rank applicants?”
Identify skill gaps for internal promotions
“I'm considering promoting someone to our data science team. Their background has Python, basic statistics, and SQL experience, but the role needs Python, advanced ML, statistical modeling, and Tableau. What are they missing and how close are they to being ready?”
Validate contractor qualifications for projects
“We just got a proposal from a contractor claiming expertise in React, Node.js, PostgreSQL, Docker, and CI/CD pipelines. Our project requires React, JavaScript, databases, containerization, and DevOps. Can you match their claimed skills against what we actually need and give me a confidence score on whether they're a fit?”
Technical details
Endpoint
GEThttps://api.strale.io/x402/skill-gap-analyze?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need automated, fuzzy skill matching between a job's requirements and a candidate's skill set — especially useful in agentic hiring workflows, ATS integrations, or resume screening pipelines where partial/synonym matches (e.g. 'JS' vs 'JavaScript') should still count.
Side effects
- Missing required_skills or candidate_skills arrays returns a 400/422 validation error
- Empty arrays for either parameter may return a zero match score or error
- Malformed array inputs may cause schema validation failure
- Network timeouts or service unavailability return 5xx errors
Input
{
"required_skills": [
"Python",
"SQL",
"Machine Learning",
"Data Visualization",
"Statistics"
],
"candidate_skills": [
"Python",
"pandas",
"SQL",
"Tableau",
"Excel"
]
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Output
{
"_meta": {
"payment": {
"method": "x402",
"price_usd": 0.162,
"settlement_id": "0x069600819cd0b9d25931f1480ad34200420d1cc0866a1db17db9e2f350bfca52"
},
"capability": "skill-gap-analyze",
"latency_ms": 0,
"provenance": {
"source": "algorithmic",
"fetched_at": "2026-06-16T01:23:56.267Z"
}
},
"extra": [
"pandas",
"Tableau",
"Excel"
],
"matched": [
{
"exact": true,
"found": "Python",
"required": "Python"
},
{
"exact": false,
"found": "SQL",
"required": "SQL"
}
],
"missing": [
"Machine Learning",
"Data Visualization",
"Statistics"
],
"summary": "Weak match: only 2/5 required skills present. Major gaps: Machine Learning, Data Visualization, Statistics.",
"fuzzy_matches": [
{
"found": "SQL",
"required": "SQL",
"confidence": 0.9
}
],
"total_required": 5,
"total_candidate": 5,
"match_score_percent": 40
}Tags
x402
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