A diagnostic tool for identifying flaky GitHub Actions workflows by analyzing failure rates across specific trigger events and repositories.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-actions-trigger-health-audit
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install github-actions-trigger-health-audit using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is GitHub Actions Trigger Health Audit?
This skill provides developers and DevOps teams with a systematic way to audit the reliability of their automation pipelines. By parsing GitHub Actions run data, it exposes which specific event triggers—such as push, pull_request, or schedule—are most prone to failure, allowing teams to prioritize fixes for noisy or unstable CI/CD workflows. It effectively bridges the gap between raw execution logs and actionable maintenance insights. Integrating Openclaw Skills like this into your workflow enables a data-driven approach to maintaining infrastructure health and reducing developer friction caused by false positives in CI.
GitHub Actions Trigger Health Audit Use Cases
- Identifying flaky workflows that fail intermittently on specific branch patterns or event types.
- Auditing CI/CD costs by identifying expensive, high-failure automated triggers.
- Benchmarking workflow performance and runtime across multiple repositories.
- Setting up automation gates that fail builds or notify teams when workflow failure rates exceed critical thresholds.
How GitHub Actions Trigger Health Audit Works
- Collect GitHub Actions run data in JSON format using the GitHub CLI (gh).
- Configure audit parameters such as failure thresholds, regex filters for workflows, and the data glob pattern.
- Execute the audit script to parse, group, and analyze the collected JSON artifacts.
- Review the generated report or JSON output to identify hotspots where failure rates exceed warning or critical levels.
- Optionally integrate the audit into CI pipelines as a quality gate to prevent further degradation of automation health.
GitHub Actions Trigger Health Audit Setup
First, ensure you have bash and python3 installed in your environment. Collect the necessary run data using the GitHub CLI:
gh run view <run-id> --json databaseId,workflowName,event,conclusion,headBranch,headSha,createdAt,updatedAt,startedAt,url,repository > artifacts/github-actions/run-<run-id>.json
Then, execute the audit using the Openclaw Skills scripts provided in the repository:
RUN_GLOB='artifacts/github-actions/*.json' \
MIN_RUNS=3 \
FAIL_WARN_PERCENT=25 \
FAIL_CRITICAL_PERCENT=50 \
bash skills/github-actions-trigger-health-audit/scripts/trigger-health-audit.sh
GitHub Actions Trigger Health Audit Data Schema & Taxonomy
The skill processes JSON files exported from the GitHub API and organizes data into a structured format for analysis:
| Attribute | Description |
|---|---|
| repository | The source repository for the workflow run |
| event | The trigger event (e.g., push, pull_request, schedule) |
| workflowName | The name of the GitHub Action workflow |
| conclusion | The final state (success, failure, cancelled, timed_out) |
| metrics | Calculated failure, cancel, and timeout rates plus average runtime |
GitHub Actions Trigger Health Audit Advanced Features
- Regex-based filtering for precise control over which repositories, workflows, or events are included in the audit.
- Configurable thresholding for warning and critical failure percentages to match team SLOs.
- Support for automation gates via the FAIL_ON_CRITICAL environment variable for CI/CD integration.
- Flexible output formats (Text or JSON) designed for both human readability and programmatic dashboard ingestion.
- Capability to process high volumes of historical run data using standard glob pattern matching.
SKILL.md
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