Skill Gap Analysis

Compare the skills a role needs with a candidate's, with fuzzy matching. Returns matched, missing and extra skills and a match score.

Pay by wallet (x402) skill-gap-analyze

Example

Example answer

{
  "extra": [],
  "matched": [
    {
      "exact": true,
      "found": "test_item",
      "required": "test_item"
    }
  ],
  "missing": [],
  "summary": "All required skills are matched by the candidate.",
  "fuzzy_matches": [],
  "total_required": 1,
  "total_candidate": 1,
  "match_score_percent": 100
}

Inputs

Field	Type	Required	What it is
`required_skills`	array	Yes	—
`candidate_skills`	array	Yes	—

Output fields

How reliably each field appears in a successful answer.

Field	Type	Appears
`extra`	array	Always (present in every successful answer)
`matched`	array	Always (present in every successful answer)
`missing`	array	Always (present in every successful answer)
`match_score_percent`	number	Always (present in every successful answer)

How to call it

The same tool through each route. MCP clients reach it through Strale’s server at https://api.strale.io/mcp; the call below is what the agent sends.

# Needs an API key. max_price_cents caps what this call may cost.
curl -X POST https://api.strale.io/v1/do \
  -H "Authorization: Bearer $STRALE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "capability_slug": "skill-gap-analyze",
    "inputs": {
      "required_skills": [
        "test_item"
      ],
      "candidate_skills": [
        "test_item"
      ]
    },
    "max_price_cents": 15
  }'

{
  "tool": "strale_execute",
  "arguments": {
    "slug": "skill-gap-analyze",
    "inputs": {
      "required_skills": [
        "test_item"
      ],
      "candidate_skills": [
        "test_item"
      ]
    },
    "max_price_cents": 15
  }
}

import { Strale } from "straleio";

const strale = new Strale({ apiKey: process.env.STRALE_API_KEY! });
const result = await strale.do({
  capability_slug: "skill-gap-analyze",
  inputs: {
    "required_skills": [
      "test_item"
    ],
    "candidate_skills": [
      "test_item"
    ]
  },
  max_price_cents: 15,
});

import os
from straleio import Strale, DoRequest

strale = Strale(api_key=os.environ["STRALE_API_KEY"])
result = strale.do(DoRequest(
    capability_slug="skill-gap-analyze",
    inputs={
        "required_skills": [
            "test_item",
        ],
        "candidate_skills": [
            "test_item",
        ],
    },
    max_price_cents=15,
))

# No account. The first request answers 402 with the price in USDC;
# an x402 client pays it from your wallet and repeats the request.
curl -i -X POST https://api.strale.io/x402/v2/skill-gap-analyze \
  -H 'Content-Type: application/json' \
  -d '{
    "required_skills": [
      "test_item"
    ],
    "candidate_skills": [
      "test_item"
    ]
  }'

Limitations

Proficiency and certifications are not measured
Gap analysis based on AI assessment of skill descriptions — does not measure actual proficiency or certification status
What to do instead: Use as a starting point for development planning and validate critical gaps with skills assessments or interviews