Does it work with large log files?

Absolutely. It uses efficient filtering techniques like grep and tail to extract relevant error segments, avoiding memory issues while ensuring no critical context is missed.

Can it identify flaky tests versus real regressions?

Yes, by analyzing failure patterns and environmental context, it helps distinguish between transient infrastructure issues and deterministic code failures.

How does the skill access my CI logs?

The skill utilizes command-line tools like the GitHub CLI (gh) to view or download workflow run logs and artifacts directly into the environment for analysis.

Can it fix the broken code automatically?

This skill focuses on analysis and root cause identification. Once the cause is found, it provides recommendations that can be implemented using related code-fixing skills.

What types of errors can it categorize?

It specifically identifies compilation errors, test assertions, timeouts, dependency version conflicts, and environmental resource issues like 'out of memory' errors.

CI Failure Log Analyzer

Name: CI Failure Log Analyzer
Author: HomericIntelligence

byHomericIntelligence

•

Despliegue y DevOps

Diagnoses and categorizes Continuous Integration build failures by parsing logs to identify root causes and remediation steps.

The CI Failure Log Analyzer skill automates the tedious process of debugging broken CI pipelines by scanning output from environments like GitHub Actions. It intelligently extracts error messages, stack traces, and failure patterns to distinguish between code regressions, environmental constraints, and dependency conflicts. By mapping failures back to recent pull request changes, it provides developers with actionable summaries and specific remediation steps, significantly reducing the time spent manually searching through thousands of lines of build output.

Características Principales

0114 GitHub stars

02Intelligent error categorization including compilation, test, and timeout issues

03Automated log parsing from GitHub Actions and build artifacts

04Root cause identification with line-number and stack trace mapping

05Actionable remediation reports linked to specific code changes

06Pattern recognition for recurring infrastructure or dependency conflicts

Casos de Uso

01Debugging a failed GitHub Actions run to pinpoint specific test regressions

02Determining if a build failure is caused by code changes or flaky infrastructure

03Summarizing voluminous error logs from build artifacts to identify hidden exceptions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add homericintelligence/projectodyssey analyze-ci-failure-logs

For use in Claude.ai and ChatGPT

Download Skill