A DevOps tool that analyzes GitHub Actions history to identify and score risky deployment workflows before production releases.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-actions-deploy-risk-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-deploy-risk-audit using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
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What is GitHub Actions Deploy Risk Audit?
The GitHub Actions Deploy Risk Audit is a specialized utility designed to enhance CI/CD reliability by quantifying the health of deployment pipelines. By processing JSON exports of action runs, this tool identifies patterns of failure, unresolved streaks, and stale deployment windows, providing a clear risk score for every release workflow. As part of the Openclaw Skills ecosystem, it bridges the gap between raw build logs and actionable engineering intelligence.
This skill enables teams to move beyond binary pass/fail results, offering a nuanced view of repository stability. It helps DevOps engineers and SREs establish automated release gates based on historical reliability rather than just the latest commit status, ensuring that production environments are protected from unstable deployment patterns.
GitHub Actions Deploy Risk Audit Use Cases
- Auditing production release workflows for recurring failure patterns and instability.
- Implementing a fail-fast release gate in CI/CD pipelines when deployment risk scores exceed safety thresholds.
- Identifying stale deployment pipelines that have not seen a successful run within a specified timeframe.
- Visualizing team-wide deployment health across multiple repositories and branches for engineering leadership.
How GitHub Actions Deploy Risk Audit Works
- Collect GitHub Actions run data using the GitHub CLI (gh) in JSON format for the targeted workflows.
- Filter workflows based on configurable regex patterns, specifically matching terms like deploy, release, or production.
- Group the collected run data by repository name, workflow title, and branch to isolate specific release tracks.
- Calculate a weighted risk score based on three primary metrics: failure rates, trailing failure streaks, and days since the last successful execution.
- Compare the calculated score against user-defined warning and critical thresholds.
- Generate a human-readable text report or a machine-readable JSON output for further automation and dashboarding.
GitHub Actions Deploy Risk Audit Setup
Ensure you have bash and python3 installed on your system. First, use the GitHub CLI to collect your workflow run data into the expected directory:
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 script structure:
RUN_GLOB='artifacts/github-actions/*.json' \
DEPLOY_WORKFLOW_MATCH='(?i)(deploy|release)' \
MIN_RUNS=3 \
bash skills/github-actions-deploy-risk-audit/scripts/deploy-risk-audit.sh
GitHub Actions Deploy Risk Audit Data Schema & Taxonomy
This skill consumes standard GitHub run JSON objects and produces a structured risk assessment. The scoring logic evaluates the following data points:
| Metric | Description |
|---|---|
| failure_rate | The percentage of failed runs within the analyzed sample |
| failure_streak | The number of consecutive failures leading up to the most recent run |
| staleness | Total days elapsed since the last successful deployment run |
| total_runs | The volume of data points analyzed for the specific workflow group |
The tool can output a JSON schema containing a summary of critical findings and a detailed scored_groups list for integration with external monitoring tools.
GitHub Actions Deploy Risk Audit Advanced Features
- Custom Regex Filtering: Use REPO_MATCH and BRANCH_EXCLUDE to fine-tune exactly which pipelines are audited.
- Automated Release Gates: Set FAIL_ON_CRITICAL=1 to force a non-zero exit code when high-risk workflows are detected, stopping unsafe deployments in their tracks.
- Flexible Scoring: Adjust sensitivity by modifying WARN_SCORE and CRITICAL_SCORE variables to match your team's risk tolerance.
- CI Dashboard Integration: Utilize the JSON output format to feed Openclaw Skills data directly into custom DevOps dashboards or reporting suites.
SKILL.md
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