crash-fixerAutonomous crash analysis and bug fixing. Monitors crash reports from Cloudflare D1, deduplicates, analyzes with Codex 5.3 High, generates fixes, and creates...
Install via ClawdBot CLI:
clawdbot install Ryce/crash-fixerFull autonomous crash-fixing loop. Fetches crashes, deduplicates, analyzes with AI, generates fixes, and creates PRs.
/crash-fixer [--hours 24] [--limit 5] [--dry-run]
| Flag | Default | Description |
|------|---------|-------------|
| --hours N | 24 | Only fetch crashes from last N hours |
| --limit N | 3 | Max crashes to process per run |
| --dry-run | false | Analyze but don't create PRs |
| Variable | Description |
|----------|-------------|
| GH_TOKEN | GitHub API token |
| CRASH_REPORTER_API_KEY | API key for crash reporter worker |
| CRASH_REPORTER_URL | URL of crash reporter worker |
| TARGET_REPO | GitHub repo to fix (owner/name) |
Note: Uses MiniMax M2.5 (available in OpenClaw) for AI analysis - no extra API key needed.
/crash-fixer --dry-run
Generated Mar 1, 2026
A cloud-based SaaS company uses this skill to automatically process crash reports from its production environment. It reduces manual debugging time by autonomously analyzing and fixing common crashes, ensuring high uptime and customer satisfaction.
An e-commerce platform integrates this skill to monitor and fix crashes in real-time during peak shopping seasons. It helps prevent revenue loss by quickly addressing issues like checkout failures or page load errors without developer intervention.
A mobile app development team employs this skill to handle crash reports from backend services. It automates the fix cycle for recurring bugs, allowing developers to focus on new features rather than firefighting stability issues.
A fintech company uses this skill to ensure compliance and reliability by automatically fixing crashes in transaction processing systems. It minimizes downtime and security risks by quickly patching vulnerabilities identified through crash analysis.
Offer this skill as part of a premium support package for businesses, charging a monthly fee for autonomous crash fixing. It provides predictable revenue while reducing customer churn through improved service reliability.
Implement a usage-based pricing model where clients pay for each crash fixed by the skill. This appeals to smaller companies with sporadic issues, generating revenue aligned with actual value delivered.
License the skill to large enterprises for integration into their internal DevOps pipelines. Charge an annual fee based on the scale of deployment, ensuring steady income from long-term contracts.
💬 Integration Tip
Ensure all required environment variables are securely configured in your CI/CD pipeline, and test with --dry-run first to validate analysis without creating PRs.
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