How does this skill help with production errors?

It leverages observability data from tools like Sentry and DataDog to correlate logs and traces, helping identify the root cause of production issues without invasive changes.

How does it handle intermittent or non-reproducible issues?

It employs statistical analysis, chaos engineering principles, and time-travel debugging strategies to isolate rare failure patterns and edge cases.

What observability platforms are supported?

It is designed to interpret data from major platforms including Sentry, Rollbar, DataDog, New Relic, ELK stack, and OpenTelemetry-compatible tools.

Can it suggest actual code fixes?

Yes, it generates proposed code changes along with a risk assessment, impact analysis, and specific validation steps to ensure the fix is effective.

Does it support local debugging workflows?

Absolutely; the skill provides tailored strategies for interactive debugging using tools like VS Code and Chrome DevTools for reproducible local issues.

Smart Error Diagnostics & Debugging

Name: Smart Error Diagnostics & Debugging
Author: sickn33

bysickn33

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34,777

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分析と監視

Diagnoses complex software errors using AI-powered root cause analysis and observability data integration.

This skill transforms Claude into an expert debugging specialist capable of handling everything from local crashes to intermittent production outages. By integrating with modern observability platforms like Sentry and DataDog, it analyzes stack traces, generates ranked hypotheses, and recommends production-safe instrumentation. It guides users through the entire lifecycle of an issue—from initial triage and evidence collection to fix implementation and the creation of regression tests—ensuring high-reliability code through automated, data-driven diagnostics.

主な機能

01Automated Root Cause Analysis (RCA) and execution path reconstruction

02AI-powered hypothesis generation with evidence-based probability scoring

0334,777 GitHub stars

04Automated fix generation with impact assessment and validation plans

05Guidance on production-safe debugging and dynamic instrumentation techniques

06Deep integration with observability tools like Sentry, DataDog, and New Relic

ユースケース

01Identifying the source of complex race conditions or state management failures in staging

02Diagnosing performance regressions such as N+1 query patterns in database interactions

03Troubleshooting intermittent production timeouts using distributed traces and APM metrics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sickn33/antigravity-awesome-skills error-diagnostics-smart-debug

For use in Claude.ai and ChatGPT

主な機能

01Automated Root Cause Analysis (RCA) and execution path reconstruction

02AI-powered hypothesis generation with evidence-based probability scoring

0334,777 GitHub stars

04Automated fix generation with impact assessment and validation plans

05Guidance on production-safe debugging and dynamic instrumentation techniques

06Deep integration with observability tools like Sentry, DataDog, and New Relic

ユースケース

01Identifying the source of complex race conditions or state management failures in staging

02Diagnosing performance regressions such as N+1 query patterns in database interactions

03Troubleshooting intermittent production timeouts using distributed traces and APM metrics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sickn33/antigravity-awesome-skills error-diagnostics-smart-debug

For use in Claude.ai and ChatGPT