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Strale Skill Gap Analyzer
x402
Strale 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 2026-09-14).
Analyzes the gap between required job skills and a candidate's existing skills, returning a structured breakdown of missing, matching, and partial competencies.
Price / call$0.162
Success—
StatusUnknown
How this service works
The trust layer for AI agents — 250+ independently tested data capabilities across 27 countries. Execute capabilities via REST, MCP, A2A, or x402 micropayments. Every call returns an audit record with cryptographic chain hashing.
Output
Returns a structured breakdown of matching skills, missing skills, and partial overlaps between the required skills list and the candidate's skills list, along with a summary assessment of the overall competency gap.
Example use cases
Candidate screening for a technical role
“I'm hiring a data engineer and need to know how well this candidate stacks up. The role requires Spark, Python, SQL, Kafka, and cloud architecture. The candidate lists Python, SQL, and some AWS experience. Can you tell me what's missing?”
Employee upskilling planning
“I want to help my marketing analyst grow into a data scientist role. The data scientist role needs machine learning, Python, statistics, and data storytelling. My analyst currently knows Excel, basic statistics, and SQL. What skills do they need to develop?”
Job application readiness check
“I'm applying for a product manager job that requires agile methodology, roadmap planning, stakeholder management, and SQL. I have experience with roadmap planning and stakeholder management but not the others. How big is my skill gap?”
Technical details
Endpoint
GEThttps://api.strale.io/x402/v2/skill-gap-analyzeWhen to prefer
Use this endpoint when you need a structured, auditable comparison between a job's required skills and a candidate's or employee's current skills. It is ideal for HR automation pipelines, ATS integrations, and learning & development workflows where a cryptographically verifiable audit record of the assessment is needed. Prefer this over generic LLM prompting when you need consistent, repeatable skill gap outputs across many candidates.
Side effects
- Empty or missing required_skills parameter returns an error
- Empty or missing candidate_skills parameter returns an error
- Ambiguous or very short skill lists may produce low-confidence or generic gap assessments
- Skills described in very different terminology may not be correctly matched even if semantically equivalent
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| required_skills | string | |
| candidate_skills | string |
Tags
x402
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