Découvrez les skills research llm ai, comparez leurs dépôts et consultez leurs instructions.
Generate project-level AGENTS.md guides that capture conventions, workflows, and required follow-up tasks. Use when a repository needs clear agent onboarding covering structure, tooling, testing, task flow, REA...
Generate complete, production-ready MCP (Model Context Protocol) servers with automatic setup, configuration, and Claude Code integration
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications.
Create useful, informative summaries of technologies or concepts that are readable in depth and have a digestable summary at the top.
Build custom slash commands in Claude Code with YAML frontmatter, permissions, and best practices. Use when creating automation workflows, project-specific commands, or standardizing repetitive tasks.
Build event-driven hooks in Claude Code for validation, setup, and automation. Use when you need to validate inputs, check environment state, or automate tasks at specific lifecycle events.
Review AI prompts and instructions for conciseness and clarity. Use when reviewing skills, CLAUDE.md, slash commands, or any LLM prompt content.
A meta-skill for documenting and creating reusable skills for Claude Code agents. Use when you discover a technique, pattern, or workflow worth documenting for reuse across projects.
Create native Claude Code hooks in ~/.claude/hooks/. Use when adding event-triggered automation (PreToolUse, PostToolUse, Stop, etc.).
Create custom Task subagents in ~/.claude/agents/. Use when defining new agents for Task tool delegation.
Create slash commands for user-initiated workflows. Use when building repeatable /name commands for Claude Code.
Route tasks to optimal LLM provider (Gemini, Codex, Copilot, Claude)
Create skills that extend Claude with specialized knowledge and workflows. Use when Claude needs to learn a methodology or approach.
Store universal coding patterns and insights into file-based memory. Use after completing difficult tasks with broadly-applicable lessons that work across ANY project. Use when user says "--coder-store" or "--l...
Retrieve project-specific insights from file-based memory. Use when working on features, encountering domain-specific questions, or user says "--project-recall" or "--recall" (you decide which scope, may use bo...
Retrieve universal coding patterns from file-based memory. Use when starting complex tasks, encountering unfamiliar problems, or user says "--coder-recall" or "--recall" (you decide which scope, may use both)....
Retrieve universal coding patterns from vector database. Use when starting complex tasks, encountering unfamiliar problems, or user says "--coder-recall" or "--recall" (you decide which scope, may use both). Sk...
Store project-specific insights and context into file-based memory. Use after completing tasks that reveal important details about THIS codebase. Use when user says "--project-store" or "--learn" (you decide wh...
Retrieve universal coding patterns from vector database using true two-stage retrieval. Auto-invokes before complex tasks or when user says "--recall". Searches relevant role collections based on task context.
Store universal coding patterns and insights into vector database. Use after completing difficult tasks with broadly-applicable lessons that work across ANY project. Use when user says "--coder-store" or "--lea...
Store universal coding patterns into vector database. Auto-invokes after difficult tasks with broadly-applicable lessons. Trigger with "--store" or when user expresses frustration (strong learning signals). Use...
Rails service object patterns and business logic organization. Automatically invoked when working with service objects, extracting business logic, implementing command/query patterns, or organizing app/services...
Designing effective prompts - system/user prompts, few-shot learning, chain-of-thought, defensive prompting, injection defense. Use when crafting prompts, improving outputs, or securing AI applications.
AI agent follows implementation plans systematically with progress tracking, quality gates, and blocker resolution. Use when implementing features, following plans, or executing tasks.
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.