Pipeline Error Fix

Pipeline Error Fix

Overview

This skill provides a systematic approach to identifying and resolving failures in automated pipelines (GitHub Actions, Jenkins, etc.).

When to Use

• When a CI/CD build or test run fails.
• When deployment pipelines encounter environment-specific errors.
• When structural regressions are detected during a build process.

Prerequisites

• Access to the pipeline logs.
• conda environment cursor-factory active.
• Understanding of the debug-pipeline workflow.
• Basic knowledge of the target pipeline's configuration (e.g., .github/workflows/).

Process

1. Analyze Logs: Use grep or specialist agents to identify the first failing step.
2. Decompose Strategy: Determine if the failure is code-related (tests), configuration-related (paths), or infrastructure-related (timeouts).
3. Execute Workflow: Trigger the /debug-pipeline workflow or follow the manual steps in .agent/workflows/debug-pipeline.md.
4. Apply Fix: Implement the targeted fix.
5. Verify: Re-run the local verification suite (e.g., pytest) before pushing.

Best Practices

• Isolation: Fix one failure at a time to avoid complex regressions.
• Verification: Always run pytest locally before letting the CI handle it.
• Root Cause: Don't just patch the symptom; use the "5 Whys" to find the root cause.
• Documentation: Document the fix and any learned patterns in a Knowledge Item or the references/ directory.

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