analyze-github-action-logs
Analyze recent GitHub Actions workflow runs to identify patterns, mistakes, and improvements. Use when asked to "analyze workflow logs", "review action runs", or "analyze GitHub Actions".
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/withastro/astro --skill analyze-github-action-logs- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads analyze-github-action-logs automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Analyze GitHub Action Logs
Fetch and analyze recent GitHub Actions runs for a given workflow. Review agent/step performance, identify wasted effort and mistakes, and produce a report with actionable improvements.
Input
You need:
workflow(required) — The workflow file name or ID (e.g.,issue-triage.yml,deploy.yml).repo(optional) — The GitHub repository inOWNER/REPOformat. Defaults towithastro/astro.count(optional) — Number of recent completed runs to analyze. Defaults to5.
Step 1: List Recent Runs
Fetch the most recent completed runs for the workflow. Filter by --status=completed:
gh run list --workflow=<workflow> -R <repo> --status=completed -L <count>
Present the list to orient yourself: run IDs, titles, status (success/failure), and duration. Pick the runs to analyze — prefer a mix of successes and failures if available, and prefer runs that exercised more steps (longer runs tend to go through more stages, while shorter runs may exit early).
Step 2: Fetch Logs
For each run you want to analyze, save the full log to a temp file:
gh run view <run_id> -R <repo> --log > /tmp/actions-run-<run_id>.log
Step 3: Identify Step/Skill Boundaries
Search each log file for markers that indicate where each step or skill starts and ends. The markers depend on the workflow — look for patterns like:
- Flue skill markers:
[flue] skill("..."): starting/completed - GitHub Actions step markers: Step name headers in the log output
- Custom markers: Any
START/ENDor similar delimiters the workflow uses
grep -n "skill(\|step\|START\|END\|starting\|completed" /tmp/actions-run-<run_id>.log | head -50
From this, determine which line ranges correspond to each step/skill. Also find any result markers:
grep -n "RESULT_START\|RESULT_END\|extractResult" /tmp/actions-run-<run_id>.log
Note: Some log files may contain binary/null bytes. Use grep -a if needed.
Step 4: Analyze Each Step (Use Subagents)
For each step/skill that ran, launch a subagent to analyze that section's log. This is critical to avoid polluting your context with thousands of log lines.
For each subagent, provide:
- The log file path and the line range for that step
- If skill instruction files exist for the workflow, tell the subagent to read them first for context
- The run title/context so the subagent understands what was being done
- The analysis criteria below
Analysis Criteria
Tell each subagent to evaluate:
- Correctness — Was the step's final result/verdict correct?
- Efficiency — How long did it take? What's a reasonable baseline? Where was time wasted?
- Mistakes — Wrong tool calls, failed commands retried without changes, unnecessary rebuilds, etc.
- Instruction compliance — If skill instructions exist, did the agent follow them? Where did it deviate?
- Scope creep — Did the agent do work that belongs in a different step?
- Suggestions — Specific, actionable changes that would prevent the issues found.
Tell each subagent to return a structured response with: Summary, Time Analysis, Issues Found (with estimated time wasted for each), and Suggestions for Improvement.
Step 5: Consolidate Report
After all subagents return, synthesize their findings into a single report. Structure it as:
Per-Run Summary Table
For each run analyzed, include a table:
| Step/Skill | Time | Result | Time Wasted | Top Issue |
|---|
Cross-Cutting Patterns
Identify issues that appeared across multiple runs or multiple steps. These are the highest-value improvements. Common patterns to look for:
- TodoWrite abuse — Agent wasting time on task list management during automated runs
- Server management failures — Port conflicts, failed process kills, stale log files
- Tool misuse — Using
curlinstead ofgh,jqnot found, etc. - Scope creep — One step doing work that belongs in another
- Unnecessary rebuilds — Building packages multiple times without changes
- Test timeouts — Running slow E2E/Playwright tests that time out
- Instruction violations — Agent doing something the instructions explicitly forbid
- Redundant work — Re-reading files, re-running searches, re-installing dependencies
Prioritized Recommendations
Rank your improvement suggestions by estimated time savings across all runs. For each recommendation:
- What to change — Which file(s) to edit and what to add/modify
- Why — What pattern it addresses, with evidence from the runs
- Estimated impact — How much time it would save per run
Output
Present the full consolidated report. Do NOT edit any workflow or skill files — only report findings and recommendations. The user will decide which changes to apply.
FAQ
What does the analyze-github-action-logs skill do?
Analyze recent GitHub Actions workflow runs to identify patterns, mistakes, and improvements. Use when asked to "analyze workflow logs", "review action runs", or "analyze GitHub Actions".
How do I install analyze-github-action-logs?
Run npx skills add https://github.com/withastro/astro --skill analyze-github-action-logs in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/analyze-github-action-logs/ (personal) or .claude/skills/analyze-github-action-logs/ (project).
Which AI agents can use analyze-github-action-logs?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is analyze-github-action-logs safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains analyze-github-action-logs?
It is published by withastro in withastro/astro. It has 382 recorded installs.
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