NAKONETS CI Triage - GitHub Actions Log Analyzer

x402

NAKONETS CI Triage - GitHub Actions Log Analyzer is a paid API for AI agents from x402vercel.vercel.app, paid per call via x402, $0.5/call, status unknown (last checked 2026-10-02).

Analyzes GitHub Actions failure log text to identify root cause class and extract key error evidence snippets

Price / call$0.5

Seller volume →—

Success—

StatusUnknown

How this service works

Pay-per-call deterministic utilities for CI diagnosis, data validation, JavaScript syntax checks, market snapshots and opportunity preflight.

Output

Returns a JSON object with an 'evidence' array of extracted error strings from the log (e.g. specific failing lines or module names) and a 'rootCauseClass' string categorizing the failure type (e.g. 'dependency', 'syntax', 'configuration').

Example use cases

Automated CI failure root cause detection

“My pull request build just failed on GitHub Actions. Here's the full log output — can you triage it and tell me whether this is a dependency issue, a syntax problem, or something else, and point out the specific lines that indicate the problem?”

Agent-driven CI triage in deployment pipeline

“Before I retry this deployment, analyze this GitHub Actions failure log and classify what broke — I need to know the root cause category and the evidence lines so I can decide whether to rerun or fix the code first.”

Developer debugging failed test suite run

“My test suite is failing in CI and I can't figure out why just from skimming the log. Can you run this through CI triage and extract what's actually causing the failure and what class of error it is?”

Technical details

Endpoint

POSThttps://x402vercel.vercel.app/api/ci/triage?utm_source=zero.xyz

When to prefer

Choose this endpoint when you have a raw GitHub Actions failure log and need a fast, deterministic classification of the root cause category along with extracted evidence lines — particularly useful in automated agent workflows where you want to branch logic based on failure type (e.g. retry on flaky test vs fix dependency vs fix syntax) without manual log reading.

Side effects

Empty or malformed log string returns unclear classification
Very long logs may exceed input limits or produce lower-confidence results
Ambiguous or multi-failure logs may yield a single rootCauseClass that doesn't cover all issues
Non-GitHub-Actions log formats may produce incorrect evidence extraction
Network or payment processing failures return HTTP 402 or 5xx errors

Input

Schema · Request body

Field	Type	Description
log	string	GitHub Actions failure log text

Output

Schema · Response

{
  "type": "json",
  "example": {
    "evidence": [
      "Error: Cannot find module foo"
    ],
    "rootCauseClass": "dependency"
  }
}

Reviews

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