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Actions Debugging

skill-drvoss-everything-copilot-cli-actions-debugging · by drvoss

Use when a GitHub Actions workflow fails — diagnose the run log, identify the root cause, and apply a targeted fix

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Install

$ agentstack add skill-drvoss-everything-copilot-cli-actions-debugging

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

GitHub Actions Debugging

Why This is Copilot-Exclusive

Copilot CLI provides structured access to GitHub Actions through its built-in MCP server. You can list workflows, inspect run details, download job logs, and analyze failures — all via typed tool calls that return structured data. Claude Code has no GitHub Actions integration whatsoever; debugging CI requires manually navigating the GitHub web UI or parsing raw gh run view output.

When to Use

  • A CI pipeline fails and you need to understand why — fast
  • Investigating flaky tests across multiple workflow runs
  • Auditing workflow run times and usage patterns
  • Debugging deployment pipeline failures in staging/production
  • Comparing successful vs failed runs to find regressions

Workflow

1. List Workflows in a Repository

Tool: github-mcp-server-actions_list
  method: "list_workflows"
  owner: "my-org"
  repo: "my-app"

2. List Recent Runs for a Workflow

Tool: github-mcp-server-actions_list
  method: "list_workflow_runs"
  owner: "my-org"
  repo: "my-app"
  resource_id: "ci.yml"
  workflow_runs_filter: { "status": "completed", "branch": "main" }

3. Get Failed Job Logs

This is the killer feature — pull logs directly for analysis:

Tool: github-mcp-server-get_job_logs
  owner: "my-org"
  repo: "my-app"
  run_id: 12345678
  failed_only: true
  return_content: true
  tail_lines: 200

4. Inspect a Specific Job

Tool: github-mcp-server-actions_get
  method: "get_workflow_job"
  owner: "my-org"
  repo: "my-app"
  resource_id: "98765432"

5. Check Run Usage and Timing

Tool: github-mcp-server-actions_get
  method: "get_workflow_run_usage"
  owner: "my-org"
  repo: "my-app"
  resource_id: "12345678"

Examples

"Why Did My CI Fail?"

> "My latest push to feature/auth-refactor failed CI. Show me what went wrong."

Copilot workflow:

  1. list_workflow_runs filtered by branch feature/auth-refactor
  2. Takes the most recent failed run
  3. list_workflow_jobs to find which job(s) failed
  4. get_job_logs with failed_only: true to pull the error output
  5. Analyzes the logs, identifies the root cause, suggests a fix

All in one conversational turn — no browser tabs needed.

Flaky Test Investigation

> "The 'integration-tests' workflow has been flaky on main this week. > Show me the failure pattern."

Tool: github-mcp-server-actions_list
  method: "list_workflow_runs"
  owner: "my-org"
  repo: "my-app"
  resource_id: "integration-tests.yml"
  workflow_runs_filter: { "branch": "main" }
  per_page: 20

Copilot lists the last 20 runs, identifies which failed, pulls logs for each failure, and looks for common error patterns (e.g., timeout, race condition, external service unavailability).

Deployment Pipeline Audit

> "Show me all production deployment runs this month and flag any that took > longer than 15 minutes."

Copilot lists runs, checks usage/timing for each, and highlights anomalies.

Fix and Verify Loop

  1. Copilot reads the failure logs
  2. Identifies the broken test or build step
  3. Makes the fix in your local codebase
  4. You push the fix
  5. Copilot monitors the new run via list_workflow_runs
  6. Confirms the fix worked or continues debugging

Tips

  • Use failed_only: true: Skip successful job logs and go straight to the

failures. Saves context window space.

  • Tail the logs: Use tail_lines: 100-300 to focus on the end of the log

where errors typically appear.

  • Parallel job analysis: When a run has multiple failed jobs, call

get_job_logs on each in parallel.

  • Compare runs: Pull logs from both a passing and failing run to diff them

and isolate what changed.

  • Combine with PR tools: After fixing a CI failure, use pull_request_read

with get_check_runs to verify the fix passes on the PR.

  • Track flaky tests in SQL: Store failure patterns in the session database

to build a flakiness report over time.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.