GitHub Actions CI/CD Failure Investigator
Diagnose GitHub Actions CI/CD failures, identify root causes from logs, and generate corrected YAML workflows.
$5
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Example session with this skill installed
My CI failed on the 'build' step. Here is my workflow YAML and the log snippet showing 'Error: Process completed with exit code 127' and 'sh: 1: npm: not found'.
- Read your context and instructions
- Compiled the github actions ci
The failure was caused by a missing environment setup in the runner. The workflow attempted to execute npm before the Node.js runtime was initialized.
Failure Analysis
| Metric | Detail |
|---|---|
| Failure Category | Environment/Runner Failure |
| Root Cause | Missing actions/setup-node step in the job configuration. |
| Evidence | sh: 1: npm: not found and exit code 127. |
| Confidence | Confirmed |
Corrected Workflow
name: CI
on: [push]
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
cache: 'npm'
- name: Install dependencies
run: npm install
- name: Run build
run: npm run build
Next steps
- Replace your
buildjob steps with the corrected YAML above. - Ensure a
package-lock.jsonexists in the root for the npm cache to function. - Commit and push to trigger a fresh workflow run.
Connects securely to your tools. The creator never sees your data.
About this skill
CI/CD failures are expensive bottlenecks that stall development cycles. When a GitHub Actions workflow fails, digging through thousands of lines of logs to find the first causal error is tedious and error-prone. This skill acts as a Senior DevOps Engineer to pinpoint the exact failure point, map it to specific evidence, and provide a verified fix.
What it does
- Error Signal Extraction identifies the earliest causal error message while ignoring secondary cascade failures.
- Root Cause Mapping connects log stack traces and exit codes to specific lines in your workflow YAML.
- Failure Classification categorizes issues across 14 domains including permissions, cache, environment, and dependencies.
- YAML Remediation generates corrected GitHub Actions configuration using least-privilege principles and minimal safe changes.
- Evidence-Backed Analysis assigns confidence levels to findings, separating confirmed facts from hypotheses.
How it works
- Input Analysis involves processing your failed job logs and the corresponding
.github/workflowsYAML file. - Failure Localization identifies the failed job, step, exit code, and failure timing.
- Fix Design creates a targeted remediation plan that explains the change and its associated risks.
- Correction Generation outputs the updated YAML block or full file with preserved working steps.
Frameworks & tools
This skill is purpose-built for GitHub Actions, runner environments (Ubuntu, macOS, Windows), and common CI/CD integrations like cache actions, artifact management, and secret handling.
Why this beats prompting it yourself
Generic LLMs often hallucinate fixes or recommend broad dependency upgrades that break other parts of your build. This skill enforces a strict evidence-based methodology that prioritizes the earliest causal error and requires specific confidence levels before suggesting changes.
Use cases
- Debug Permission Denied errors related to
GITHUB_TOKENor repository secret scopes. - Fix Cache Misses caused by incorrect lockfile hashing or OS-specific cache keys.
- Resolve Environment Mismatches between local development and GitHub-hosted runners.
- Repair Syntax Errors in complex matrix strategies or conditional job logic.
Known limitations
Does not have access to your private repository settings or secret values. Cannot verify if a fix passes without the user re-running the workflow in GitHub.
Cannot access private repository settings or actual secret values. Requires manual re-run to verify fixes. Limited to GitHub Actions workflows and logs.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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