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InstructLint Agent Instruction Drift Audit
x402
InstructLint Agent Instruction Drift Audit is a paid API for AI agents from instructlint.vercel.app, paid per call via x402, $1/call, status unknown (last checked 2026-09-14).
Audits a public GitHub repository's AI instructions against its implementation reality, returning a drift score, findings, and suggested patches for $1 USDC.
Price / call$1
Success—
StatusUnknown
How this service works
Audit repository AI instructions against implementation reality, preview public GitHub drift for free, and unlock evidence plus suggested patches for $1 USDC.
Output
Returns a JSON object with an 'ok' boolean, an 'audit' object containing the mode ('full' or 'preview'), a numeric drift score (0–100), and an array of findings each with a title and severity level (e.g. high/medium/low), plus a 'repository' object with the owner and repo name.
Example use cases
Pre-release AI config sanity check
“Before we ship v2, can you audit https://github.com/acmecorp/backend-api for AI instruction drift? I need to know if any documented scripts or behaviors are missing from the actual code.”
Open source repo quality review
“I'm evaluating https://github.com/some-user/cool-agent-project for contributions — can you run an InstructLint audit on it and tell me the drift score and any high-severity findings?”
Continuous agent instruction monitoring
“Check https://github.com/myteam/ai-assistant for instruction drift and flag anything where the AGENTS.md or system prompt references something that doesn't exist in the repo anymore.”
Technical details
Endpoint
POSThttps://instructlint.vercel.app/api/reportWhen to prefer
Choose this endpoint when you need to programmatically verify that a public GitHub repository's AI instructions (e.g. AGENTS.md, Copilot instructions, Cursor rules, system prompts) are consistent with its actual implementation. It is especially valuable in CI/CD pipelines, pre-release checks, or agent governance workflows where instruction drift could cause misbehavior. Prefer this over manual review when you need a structured score and actionable findings at scale.
Side effects
- Invalid or private GitHub repository URL returns an error — only public repos are supported
- Malformed URL schema field causes request rejection
- Payment of $1 USDC not fulfilled triggers a 402 response before audit is run
- Repository with no AI instruction files may return an empty findings array with low informational value
- Rate limiting or GitHub API quota issues may cause transient failures
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| repoUrl | string | Canonical public GitHub repository URL. |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"audit": {
"mode": "full",
"score": 82,
"findings": [
{
"title": "Documented script does not exist",
"severity": "high"
}
]
},
"repository": {
"name": "repository",
"owner": "owner"
}
}
}Tags
x402
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