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Skills IA data ai debugging

Découvrez les skills data ai debugging, comparez leurs dépôts et consultez leurs instructions.

Catégories: data ai debugging

2,353–2,376 sur 5,502

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GitHub

injection-vulnerabilities-ai-generated-code

harperaa

Understand how AI generates SQL injection, command injection, and XSS vulnerabilities. Use this skill when you need to learn about injection attack patterns in AI code, see real-world examples of injection vuln...

GitHub

secure-error-handling

harperaa

Implement secure error handling to prevent information leakage and provide appropriate error responses. Use this skill when you need to handle errors in API routes, prevent stack trace exposure, implement envir...

GitHub

business-logic-flaws-ai-generated-code

harperaa

Understand business logic vulnerabilities in AI code including race conditions, integer overflow, and calculation errors that pass functional tests but create security holes. Use this skill when you need to lea...

GitHub

debug

sbusso

Expert debugging methodology. Triggers on debug, investigate, fix bug, troubleshoot.

GitHub

vitest

oriolrius

Expert guidance for Vitest testing framework including unit tests, integration tests, mocking, coverage, React Testing Library integration, and TypeScript testing. Use this when writing tests for Vite-based app...

GitHub

testing-webapps

WarrenZhu050413

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

GitHub

managing-snippets

WarrenZhu050413

Comprehensive guide for managing Claude Code snippets v2.0 - discovering locations, creating snippets from files, searching by name/pattern/description, and validating configurations. Use this skill when users...

GitHub

debugging-strategies

amurata

体系的なデバッグ技術、プロファイリングツール、根本原因分析をマスターし、あらゆるコードベースや技術スタックでバグを効率的に追跡。バグ調査、パフォーマンス問題、予期しない動作の調査時に使用。

GitHub

python-performance-optimization

amurata

cProfile、メモリプロファイラー、パフォーマンスベストプラクティスを使用してPythonコードをプロファイルおよび最適化。低速なPythonコードのデバッグ、ボトルネックの最適化、アプリケーションパフォーマンスの改善時に使用...

GitHub

debugging-methodology

webdevtodayjason

Scientific debugging methodology including hypothesis-driven debugging, bug reproduction, binary search debugging, stack trace analysis, logging strategies, and root cause analysis. Use when debugging errors, a...

GitHub

exploiting-web3-smart-contracts

trilwu

Audit and exploit smart contracts and Web3 applications including reentrancy, integer overflow, access control flaws, and DeFi-specific vulnerabilities. Use when testing blockchain applications or performing sm...

GitHub

feature-audit

schuettc

Runtime behavior auditing through systematic log injection. Use when user wants to understand what code is doing at runtime, debug complex flows, or audit a process.

GitHub

feature-troubleshoot

schuettc

Systematic debugging mode with hypothesis-driven investigation. Use when user reports a bug, encounters an error, or needs help debugging a problem.

GitHub

debugger

VenTheZone

Systematic debugging and troubleshooting for code and infrastructure issues

GitHub

quality

Yuvasee

Code quality analysis through cleanup analysis and multi-perspective reviews.

GitHub

multi-llm-advisor

freitasp1

Fetches additional perspectives from OpenAI Codex and Google Gemini for architecture, review, and debugging. Transparently displays all LLM calls.

GitHub

preview-testing

freitasp1

Comprehensive E2E + Security Tests for Vercel Preview Deployments. Combines Playwright automation with Claude-in-Chrome MCP for interactive debugging. Activate on PR creation, before merge, or manual /preview-t...

GitHub

code-review

hankhsu1996

Reviews code changes for architectural fitness, extensibility, and alignment with design principles. Use when reviewing code, checking PRs, or validating implementations.

GitHub

debug

ariaxhan

Systematic debugging methodology. Auto-triggers on "bug", "error", "not working", "broken", "failing", "debug", "fix this", "why isn't", "something's wrong", or any description of unexpected behavior.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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