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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

2,377–2,400 sur 5,502

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GitHub

code-review

houke

Comprehensive code review for Fluxby - checks security, performance, and coding standards specific to the local-first financial dashboard architecture.

GitHub

cargo-llvm-lines

onbjerg

Analyzes LLVM IR to find monomorphization bloat and compile time hotspots. Use when debugging slow builds, reducing binary size, or optimizing generic code.

GitHub

ast-grep

onbjerg

Structural code search using ast-grep. Use for syntax-aware searches, finding patterns, refactoring, or when you need to understand code structure beyond plain text matching.

GitHub

codebase-analyzer

d-o-hub

Analyze implementation details, trace data flow, and explain technical workings with precise file:line references. Use when you need to understand HOW code works.

GitHub

agent-coordination

d-o-hub

Coordinate multiple specialized Skills and Task Agents through parallel, sequential, swarm, hybrid, or iterative execution strategies. Use when orchestrating multi-worker workflows, managing dependencies, or op...

GitHub

clean-code-developer

d-o-hub

Assist developers in writing clean, maintainable code following software engineering best practices. Use when conducting code reviews, refactoring code, enforcing coding standards, seeking guidance on clean cod...

GitHub

codebase-consolidation

d-o-hub

Analyze, consolidate, and document codebases through multi-perspective analysis. Use when reviewing project structure, planning refactoring, creating documentation, or assessing technical debt.

GitHub

debug-troubleshoot

d-o-hub

Systematic debugging approach for Rust async code with Tokio, Turso, and redb. Use when diagnosing runtime issues, performance problems, async deadlocks, database connection issues, or panics.

GitHub

general

d-o-hub

General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. Use when you need to perform comprehensive searches across codebase, find files that are not obvious...

GitHub

test-fix

d-o-hub

Systematic approach to diagnosing and fixing failing tests in Rust projects. Use when tests fail and you need to diagnose root causes, fix async/await issues, handle race conditions, or resolve database connect...

GitHub

test-optimization

d-o-hub

Advanced test optimization with cargo-nextest, property testing, and performance benchmarking. Use when optimizing test execution speed, implementing property-based tests, or analyzing test performance.

GitHub

ast-grep

laulauland

AST-based code searching with ast-grep. Use when searching code by syntax structure rather than text patterns, finding specific code patterns, or refactoring.

GitHub

altinity-clickhouse-expert

Altinity

ClickHouse incident response, periodic audits, and ad-hoc debugging via focused agents (run in waves). Uses ClickHouse system tables to diagnose slow queries/inserts, too many parts/merge backlog, wrong partiti...

GitHub

mcp-narsil

MichelKerkmeester

Deep code intelligence via Narsil MCP providing 76 tools for security scanning (OWASP, CWE, taint analysis), call graph analysis (CFG, DFG, callers/callees), structural queries (symbols, definitions, references...

GitHub

workflows-chrome-devtools

MichelKerkmeester

Chrome DevTools orchestrator providing intelligent routing between CLI (bdg) and MCP (Code Mode) approaches. CLI prioritized for speed and token efficiency; MCP fallback for multi-tool integration scenarios.

GitHub

javascript

bendrucker

JavaScript coding standards and best practices for JavaScript and TypeScript. Use when writing or reviewing JavaScript code, working with promises, or discussing JavaScript patterns.

GitHub

complexity-management

VilnaCRM-Org

Maintain and improve code quality using PHPInsights without decreasing quality thresholds. Use when PHPInsights fails, cyclomatic complexity is too high, code quality drops, or when refactoring for better maint...

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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