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- Claudeskillz
- Error Debugger
error-debugger_skill
- Python
8
GitHub Stars
5
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill jackspace/claudeskillz --skill error-debugger- examples.md9.5 KB
- reference.md7.4 KB
- SKILL.json11.2 KB
- SKILL.md10.1 KB
- SKILL.md.backup10.0 KB
Overview
This skill provides context-aware error debugging that searches past solutions, analyzes error messages and stack traces, and returns immediate, actionable fixes with code examples. It automatically creates regression tests for verified fixes and saves solutions to memory so the skill gets smarter over time. Use it to reduce debugging friction and recall previously effective remedies across your projects.
How this skill works
When an error is reported or a trigger phrase is used, the skill parses the error type, message, stack trace, file, and surrounding context. It searches past saved procedures for fuzzy matches, applies known error patterns, and—if needed—performs external searches as a fallback. The skill returns a clear cause explanation, a minimal code fix with before/after snippets, prevention tips, and an option to generate regression tests and save the solution for future reuse.
When to use it
- You paste a stack trace or error message (TypeError, ECONNREFUSED, CORS, 404, 500, etc.).
- You say: "debug this", "fix this error", or "why is this failing".
- A recurring bug appears and you want a tested, reusable fix.
- You want a regression test created automatically after a fix.
- You need a quick code example showing how to avoid the same failure.
Best practices
- Provide the full error message and nearby code or stack trace for accurate diagnosis.
- Confirm applied fixes locally before telling the skill to save the solution to memory.
- Tag saved solutions with language/framework and context to improve future matching.
- Let the skill generate regression tests and run them in CI to prevent regressions.
- If an external search is required, allow the skill to try at least three approaches before requesting more info.
Example use cases
- Frontend React: Fixing "Cannot read property 'map' of undefined" by adding optional chaining and default arrays.
- Backend API: Resolving ECONNREFUSED by checking service health and port configuration with example retry logic.
- CORS Troubleshooting: Suggesting precise server header changes and a minimal repro to validate.
- HTTP Errors: Diagnosing 404/500 with route checks and server-log extraction guidance.
- Automation: Creating a regression test that fails before the fix and passes afterward, and saving the procedure for reuse.
FAQ
It provides suggested code changes and can create test artifacts; applying changes to your repository requires your confirmation or an integration you authorize.
How does it learn from past fixes?
Successful fixes are saved as procedures with tags and usage metrics; future errors are matched via fuzzy search and sorted by success rate.