A diagnostic tool that analyzes GitHub Actions run history to identify specific days and hours when workflow failures cluster.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-actions-failure-hour-audit
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
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Help me install github-actions-failure-hour-audit using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
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What is GitHub Actions Failure Hour Audit?
The GitHub Actions Failure Hour Audit is a specialized analytical tool designed to help engineering teams surface recurring outage windows and staffing hotspots within their CI/CD pipelines. By processing workflow run exports, this skill identifies patterns in failures, cancellations, and timeouts that might otherwise go unnoticed in a high-volume environment. Integrating this into your Openclaw Skills workflow allows for data-driven decisions regarding infrastructure scaling and developer support.
This skill is particularly effective for teams managing complex, global development cycles where time-zone-specific infrastructure issues or scheduled maintenance windows might be causing intermittent build failures. By bucketing results into day and hour windows, it provides a temporal heatmap of repository health.
GitHub Actions Failure Hour Audit Use Cases
- Detecting recurring infrastructure flakiness during specific high-traffic hours.
- Aligning on-call rotations with peak workflow failure periods to ensure faster incident response.
- Auditing scheduled cron-based workflows that may be failing due to resource contention.
- Implementing automated CI gates that fail builds when critical failure thresholds are met in specific windows.
How GitHub Actions Failure Hour Audit Works
- The user exports GitHub Actions workflow run data into JSON format using the GitHub CLI tool.
- The skill scans the specified artifact directory for JSON files matching the defined glob pattern.
- It filters the data to isolate failure-like conclusions such as failure, cancelled, timed_out, and startup_failure.
- Failures are categorized into day-of-the-week and hour-of-the-day buckets, with an optional timezone offset applied.
- The tool calculates failure density and ranks time windows based on user-defined warning and critical thresholds.
- A final report is emitted in text for human review or JSON for programmatic consumption by dashboards.
GitHub Actions Failure Hour Audit Setup
To get started with this tool from the Openclaw Skills collection, ensure you have the required binaries and follow these steps:
# 1. Export your GitHub Actions run data
gh run view <run-id> --json databaseId,workflowName,headBranch,conclusion,createdAt,updatedAt,url,repository \
> artifacts/github-actions/run-<run-id>.json
# 2. Execute the audit script with your preferred configuration
RUN_GLOB='artifacts/github-actions/*.json' \
WARN_FAILURE_RUNS=3 \
CRITICAL_FAILURE_RUNS=6 \
TZ_OFFSET_HOURS=-5 \
bash skills/github-actions-failure-hour-audit/scripts/failure-hour-audit.sh
GitHub Actions Failure Hour Audit Data Schema & Taxonomy
The skill processes structured JSON data from GitHub and produces a ranked report. The schema focuses on the following primary attributes:
| Attribute | Description |
|---|---|
conclusion |
The final status of the run (e.g., failure, timed_out). |
createdAt |
The UTC timestamp used to determine the temporal bucket. |
TZ_OFFSET_HOURS |
Integer used to shift UTC data to local developer time. |
windows |
A ranked list of failure clusters identified by day and hour. |
critical_windows |
Specifically flagged time slots exceeding the critical threshold. |
GitHub Actions Failure Hour Audit Advanced Features
- Regex filtering: Use
WORKFLOW_MATCHorREPO_EXCLUDEto focus the audit on specific segments of your codebase. - CI Gatekeeping: Set
FAIL_ON_CRITICAL=1to use this skill as a quality gate in your own automation pipelines. - Timezone Localization: Shift UTC data using
TZ_OFFSET_HOURSto match the local working hours of your engineering team. - Flexible Thresholds: Customize what constitutes a 'Critical' window versus a 'Warning' window to match your team's SLAs.
SKILL.md
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