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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

2,161–2,184 sur 5,502

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GitHub

r3f-performance

Bbeierle12

R3F performance optimization—LOD (Level of Detail), frustum culling, instancing strategies, draw call reduction, frame budgets, lazy loading, and profiling tools. Use when optimizing render performance, handlin...

GitHub

systematic-debugging

Bbeierle12

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes. Implements scientific method for debugging with root cause analysis.

GitHub

screenshot

jonathanpeppers

Capture a screenshot of the running WPF application UI. Use this skill when asked to see, view, capture, or screenshot the current state of the WPF application's user interface.

GitHub

tree

jonathanpeppers

Get the visual tree structure of the running WPF application. Use this skill when asked to inspect, debug, or understand the element hierarchy, control structure, or layout of the WPF UI.

GitHub

codex-cli

ohbarye

OpenAI Codex CLIを使用したコードレビュー、分析、コードベースへの質問を実行する。使用場面: (1) コードレビュー依頼時、(2) コードベース全体の分析、(3) 実装に関する質問、(4) バグの調査、(5) リファクタリング提案、(6...

GitHub

network-inspection

jpoutrin

HTTP request and response analysis for debugging API calls, identifying failed requests, and understanding data flow. Use when investigating API issues, authentication problems, or data loading failures.

GitHub

console-debugging

jpoutrin

Browser console message analysis for debugging JavaScript errors, warnings, and application logs. Use when investigating frontend issues, tracking console output, or diagnosing JavaScript problems.

GitHub

qa-screenshot-validation

jpoutrin

Evaluate captured screenshots for layout issues, masked elements, and rendering problems. Use after taking screenshots to validate visual correctness and automatically resize viewport if elements are unexpected...

GitHub

typescript-style

jpoutrin

Automatic enforcement of TypeScript/JavaScript coding style, ESLint standards, type safety, and modern patterns. Use when writing TypeScript or React code to ensure strict type safety and modern ES2024+ pattern...

GitHub

buildbuddy-invocation-compare

sluongng

Compare two BuildBuddy invocation URLs or IDs to troubleshoot hermeticity/reproducibility and cache invalidation. Use when asked to diff canonical Bazel flags, find the first shared action-cache misses, inspect...

GitHub

frida-script-assistant

nblog

Designs and generates Frida JavaScript/TypeScript single-file scripts or full agents for dynamic reverse engineering on multiple platforms. Handles function hooking/tracing (Interceptor, NativeFunction, Stalker...

GitHub

rule-selector

oimiragieo

Analyzes project tech stack and recommends optimal rule configuration. Detects frameworks from package.json, requirements.txt, go.mod, and other config files. Generates custom manifest.yaml profiles for your sp...

GitHub

sentry-monitoring

oimiragieo

Sentry error tracking and performance monitoring for real-time visibility into application errors, performance issues, and release health

GitHub

repo-rag

oimiragieo

Perform high-recall codebase retrieval using semantic search and symbol indexing. Use when you need to find specific code, understand project structure, or verify architectural patterns before editing.

GitHub

chrome-devtools

oimiragieo

Chrome DevTools for AI agents. Control and inspect live Chrome browsers with performance tracing, network inspection, DOM snapshots, and automated interactions. Use for web debugging, performance analysis, and...

GitHub

recommending-rules

oimiragieo

Analyzes codebase to find gaps in rule coverage and suggests rule improvements. Compares codebase against all indexed rules to identify missing standards. Use when setting up new projects or reviewing rule cove...

GitHub

multi-ai-code-review

oimiragieo

Run multi-provider code reviews over git diffs/PR changes using headless AI CLIs (Claude Code `claude`, Google `gemini`, optionally GitHub `copilot`) and output structured findings + an optional synthesized rep...

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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