A diagnostic tool to measure how quickly GitHub Actions workflows recover from failures and identify persistent CI bottlenecks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-actions-recovery-latency-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-recovery-latency-audit using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
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What is GitHub Actions Recovery Latency Audit?
This skill provides a systematic way to audit the reliability of your CI/CD pipelines by analyzing GitHub Actions run history. It groups runs by repository, workflow, and branch to identify failure incidents—the duration between the first failure and the subsequent success—allowing teams to pinpoint which automated processes are causing the most downtime. By integrating this into your Openclaw Skills workflow, you can move beyond simple pass/fail metrics and start measuring Mean Time To Recovery (MTTR) for your developer automation.
Beyond simple reporting, the tool calculates severity scores (ok, warn, critical) for various workflow groups. This enables teams to triage engineering debt by focusing on the most unstable pipelines. It is designed to work seamlessly with JSON exports from the GitHub CLI, making it a perfect fit for automated observability pipelines.
GitHub Actions Recovery Latency Audit Use Cases
- Measuring the Mean Time to Recovery (MTTR) for critical production workflows.
- Identifying flaky or perpetually red CI/CD pipelines that remain unresolved for days.
- Implementing CI gates that fail when recovery latency exceeds established service level objectives.
- Auditing workflow performance across multiple repositories and branches to identify systemic infrastructure issues.
How GitHub Actions Recovery Latency Audit Works
- Collect GitHub Actions run data as JSON files using the standard GitHub CLI tool.
- Parse the JSON exports to group runs by repository, workflow name, branch, and event type.
- Identify failure incidents by tracking sequences of failed runs until the next success.
- Calculate recovery latency for closed incidents and the age of currently unresolved incidents.
- Assign a severity score based on user-defined time thresholds and incident counts.
- Generate a ranked report in text or JSON format for developers to review or for automated triage.
GitHub Actions Recovery Latency Audit Setup
Ensure you have bash and python3 installed in your environment. First, collect your GitHub Actions data:
gh run view <run-id> --json databaseId,workflowName,event,conclusion,headBranch,createdAt,url,repository \
> artifacts/github-actions/run-<run-id>.json
Then, execute the audit script using Openclaw Skills infrastructure:
RUN_GLOB='artifacts/github-actions/*.json' \
TOP_N=15 \
bash skills/github-actions-recovery-latency-audit/scripts/recovery-latency-audit.sh
GitHub Actions Recovery Latency Audit Data Schema & Taxonomy
The skill processes workflow run data and categorizes results using the following schema:
| Attribute | Description |
|---|---|
| Workflow Group | A unique combination of Repository, Workflow, Branch, and Event |
| Failure Incident | The window of time from the first failing run until the next successful run |
| Recovery Latency | The total duration elapsed during a closed failure incident |
| Unresolved Age | The duration since the first failure of a currently failing workflow group |
| Severity Score | A status (ok, warn, critical) derived from P95 latency and open incident counts |
GitHub Actions Recovery Latency Audit Advanced Features
- Support for regex filtering via WORKFLOW_MATCH and REPO_EXCLUDE for granular audit targeting.
- Configurable P95 latency thresholds (WARN_P95_HOURS, CRITICAL_P95_HOURS) to match custom organizational SLAs.
- Deterministic testing support using the NOW_ISO variable to simulate specific timestamps for historical analysis.
- Automated CI integration using the FAIL_ON_CRITICAL flag to block pipeline execution when recovery metrics degrade.
- Machine-readable JSON output mode for building custom dashboards or integrations within the Openclaw Skills ecosystem.
SKILL.md
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