Compétences error-diagnostics-smart-debug
🔍

error-diagnostics-smart-debug

Sûr

Debug Errors with AI-Powered Diagnostics

This skill helps developers quickly diagnose software errors by analyzing error messages, stack traces, and performance data to identify root causes and suggest fixes.

Prend en charge: Claude Codex Code(CC)
🥉 74 Bronze
1

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2

Importer dans Claude

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3

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Tester

Utilisation de "error-diagnostics-smart-debug". Analyze this error: 'Connection timeout after 30000ms' occurring in 5% of checkout requests in production

RĂ©sultat attendu:

  • Issue Summary: Intermittent connection timeout in checkout service
  • Root Cause Analysis: Likely causes - (1) External payment API latency 60%, (2) Database connection pool exhaustion 25%, (3) Network infrastructure issue 15%
  • Recommended Strategy: Query DataDog traces for payment service duration, check connection pool metrics during error windows
  • Fix Proposal: Implement circuit breaker pattern with 10s timeout, add retry with exponential backoff
  • Validation: Deploy to canary traffic, monitor error rate reduction

Utilisation de "error-diagnostics-smart-debug". Parse this stack trace: TypeError: Cannot read property 'id' of undefined at UserService.getProfile (/src/user/service.js:42:15)

RĂ©sultat attendu:

  • Root Cause: Null reference on user object - likely race condition or missing null check
  • Hypothesis 1 (75%): User record missing from database - check authentication flow
  • Hypothesis 2 (20%): Async timing issue - getProfile called before user data loaded
  • Hypothesis 3 (5%): Schema mismatch - user object structure changed
  • Recommended Fix: Add null guard: const userId = user?.id ?? throw new Error('User not found')

Audit de sécurité

Sûr
v1 • 2/24/2026

All static findings are false positives. The skill is a legitimate debugging assistant that provides guidance on error diagnostics. No external commands, cryptographic algorithms, or network reconnaissance are present. The reported patterns were markdown formatting (backticks for code) and benign workflow descriptions.

1
Fichiers analysés
200
Lignes analysées
3
résultats
1
Total des audits
Problèmes à risque moyen (1)
SKILL.md:23SKILL.md:147
Markdown Code Formatting Misidentified
Static scanner incorrectly flagged backticks (`) as Ruby/shell backtick execution. These are markdown code formatting delimiters, not shell commands.
Problèmes à risque faible (2)
SKILL.md:3SKILL.md:94
False Positive: Cryptographic Algorithm Detection
Static scanner incorrectly detected 'weak cryptographic algorithms'. The content contains no cryptographic code.
SKILL.md:134
False Positive: Network Reconnaissance Detection
Static scanner incorrectly flagged network-related discussion as reconnaissance. The skill discusses legitimate observability data collection.
Audité par: claude

Score de qualité

38
Architecture
100
Maintenabilité
87
Contenu
50
Communauté
96
Sécurité
100
Conformité aux spécifications

Ce que vous pouvez construire

Production Incident Response

Quickly diagnose production errors by analyzing error patterns and recommending debugging strategies for on-call engineers.

Development Debugging

Get AI-assisted guidance on local debugging techniques, breakpoint placement, and step-through strategies.

Performance Issue Analysis

Analyze performance traces and APM data to identify bottlenecks, N+1 queries, and resource exhaustion issues.

Essayez ces prompts

Basic Error Analysis 
Analyze this error: $ERROR_MESSAGE. What could be the root cause?
Stack Trace Analysis 
Parse this stack trace and identify the likely source of the issue: $STACK_TRACE. Provide 3 hypotheses ranked by probability.
Production Issue Debugging 
Help debug this production issue: $ISSUE_DESCRIPTION. The error frequency is $FREQUENCY in $ENVIRONMENT environment. Recommend a debugging strategy.
Fix Validation 
Review this proposed fix for the error: $ERROR and $PROPOSED_FIX. Assess the risk level and suggest validation steps.

Bonnes pratiques

  • Provide complete error context including stack traces, reproduction steps, and environment details
  • Use observability data to validate hypotheses before implementing fixes
  • Apply incremental debugging: start with simplest explanations before complex ones
  • Always validate fixes with tests and canary deployments before full rollout

Éviter

  • Blindly applying fixes without understanding root cause
  • Ignoring error frequency and impact when prioritizing debugging efforts
  • Skipping observability data collection and relying solely on code inspection
  • Deploying fixes without validation or rollback strategy

Foire aux questions

What information should I provide for best debugging results?
Provide the complete error message, full stack trace, reproduction steps, environment details (dev/staging/production), and any relevant logs or metrics.
Can this skill fix the errors automatically?
No. The skill analyzes errors and suggests possible fixes, but you must validate and implement them. Human judgment is required for production systems.
Does this skill work with all programming languages?
Yes. The skill analyzes error patterns and debugging strategies that apply broadly. Language-specific details can be included in the error context.
Can I use this for security vulnerabilities?
The skill can help analyze error patterns, but security vulnerabilities require specialized security review. Do not rely on this skill for security auditing.
How does the skill choose the debugging strategy?
It analyzes issue characteristics: reproducibility, environment, error frequency, and affected components. Interactive debugging works for local issues; observability-driven debugging is best for production.
What observability tools does this skill integrate with?
The skill references Sentry, Rollbar, Bugsnag (error tracking), DataDog, New Relic, Dynatrace (APM), Jaeger, Zipkin, Honeycomb (tracing), and ELK, Splunk, Loki (logging).

Détails du développeur

Auteur

sickn33

Licence

MIT

DĂ©pĂ´t

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/error-diagnostics-smart-debug

RĂ©f

main

Structure de fichiers

đź“„ SKILL.md