A specialized tool to detect workflow performance degradation by comparing recent failure rates against historical baselines.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-actions-failure-spike-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-failure-spike-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 Failure Spike Audit?
The GitHub Actions Failure Spike Audit is a diagnostic utility designed for engineering teams who need to maintain CI/CD stability. By analyzing GitHub Actions run data, this skill identifies sudden increases in failure rates that often signal flaky tests, broken deployment gates, or infrastructure issues before they escalate into major outages. It is an essential component within the Openclaw Skills ecosystem for teams prioritizing automated quality assurance.
It works by grouping run data by repository, workflow name, branch, and event type. It then bifurcates these groups into a recent window and a baseline window, calculating the failure rate delta. This quantitative approach allows for automated scoring, categorizing workflow health into ok, warning, or critical statuses.
GitHub Actions Failure Spike Audit Use Cases
- Identifying new flaky tests introduced in recent pull requests.
- Detecting regressions after a major dependency update or infrastructure change.
- Automating CI/CD health checks in a central observability dashboard.
- Blocking deployment pipelines if specific workflows show a critical failure spike.
How GitHub Actions Failure Spike Audit Works
- Collect GitHub Actions run data in JSON format using the GitHub CLI.
- Group the exported JSON files by repository, workflow, branch, and event type.
- Split the run history into a recent window and a baseline historical window.
- Calculate the failure rate for both windows and determine the percentage spike.
- Assign a severity level (ok, warn, critical) based on configurable percentage gates.
- Generate a text report or JSON output and optionally exit with a failure code if critical thresholds are met.
GitHub Actions Failure Spike Audit Setup
Ensure you have bash and python3 installed on your system. This skill is a standard part of the Openclaw Skills repository.
First, collect your workflow 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, run the audit script:
RUN_GLOB='artifacts/github-actions/*.json' \
RECENT_RUNS=8 \
WARN_SPIKE_PCT=12 \
bash skills/github-actions-failure-spike-audit/scripts/failure-spike-audit.sh
GitHub Actions Failure Spike Audit Data Schema & Taxonomy
The skill processes specific GitHub Actions metadata and outputs structured results based on the following run attributes:
| Attribute | Description |
|---|---|
| databaseId | Unique identifier for the run |
| workflowName | The name of the GitHub Action workflow |
| conclusion | The final status (success, failure, etc.) |
| headBranch | The branch name where the run occurred |
| repository | The repository context |
The output generates a ranked list of failure-rate spikes, providing visibility into which specific workflow/branch combinations are degrading.
GitHub Actions Failure Spike Audit Advanced Features
- Customizable failure thresholds using WARN_SPIKE_PCT and CRITICAL_SPIKE_PCT environment variables.
- Extensive regex filtering for repositories, workflows, branches, and event types to reduce noise.
- Integrated CI gate via FAIL_ON_CRITICAL to automatically halt pipelines when degradation is detected.
- Dual output formats (Text and JSON) to support both human auditing and machine-readable integrations.
- Configurable window sizes for recent vs. baseline comparison to fine-tune sensitivity based on project velocity.
SKILL.md
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