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Skills IA documentation llm ai

Découvrez les skills documentation llm ai, comparez leurs dépôts et consultez leurs instructions.

Catégories: documentation llm ai

1,321–1,344 sur 13,084

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GitHub

codex-subagent

am-will

Spawn Codex subagents via background shell to offload context-heavy work. Use for: deep research (3+ searches), codebase exploration (8+ files), multi-step workflows, exploratory tasks, long-running operations,...

GitHub

skill-creator

joelhooks

Guide for creating effective agent skills. Use when you want to create a new skill, improve an existing skill, or learn best practices for skill development. Helps codify learned patterns into reusable, discove...

GitHub

always-on-guidance

joelhooks

Always-on rule-oriented guidance for claude-plugin agents. Use to align behavior, tool usage, and model-specific defaults (GPT-5.2-code vs Opus 4.5) while avoiding deprecated bd/cass references.

GitHub

swarm-coordination

joelhooks

Multi-agent coordination patterns for OpenCode swarm workflows. Use when working on complex tasks that benefit from parallelization, when coordinating multiple agents, or when managing task decomposition. Do NO...

GitHub

swarm-coordination

joelhooks

Multi-agent coordination patterns for OpenCode swarm workflows. Use when working on complex tasks that benefit from parallelization, when coordinating multiple agents, or when managing task decomposition. Do NO...

GitHub

skill-creator

joelhooks

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or to...

GitHub

build-skill

dmmulroy

Create effective skills for OpenCode agents. Load FIRST before writing any SKILL.md. Provides required format, naming conventions, progressive disclosure patterns, and validation. Use when building, reviewing,...

GitHub

helloagents

hellowind777

【HelloAGENTS】显式调用入口。使用 /helloagents 或 $helloagents 激活。

GitHub

agentic-jujutsu

ruvnet

Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

GitHub

parallel-task

am-will

Execute plan files by launching multiple parallel subagents to complete tasks simultaneously. Triggers on explicit "/parallel-task" commands.

GitHub

using-superpowers

Trevoke

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

GitHub

planner

am-will

Create comprehensive, phased implementation plans with sprints and atomic tasks. Use when user says: "make a plan", "create a plan", "plan this out", "plan the implementation", "help me plan", "design a plan",...

GitHub

llm-council

am-will

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge in...

GitHub

add-model

giselles-ai

Add a new language model to the Giselle codebase. Use when the user wants to add, register, or integrate a new LLM model (OpenAI, Anthropic, Google) into the system.

GitHub

axiom-using-axiom

CharlesWiltgen

Use when starting any iOS/Swift conversation - establishes how to find and use Axiom skills, requiring Skill tool invocation before ANY response including clarifying questions

GitHub

coreml

CharlesWiltgen

Use when deploying custom ML models on-device, converting PyTorch models, compressing models, implementing LLM inference, or optimizing CoreML performance. Covers model conversion, compression, stateful models,...

GitHub

axiom-foundation-models-ref

CharlesWiltgen

Reference — Complete Foundation Models framework guide covering LanguageModelSession, @Generable, @Guide, Tool protocol, streaming, dynamic schemas, built-in use cases, and all WWDC 2025 code examples

GitHub

axiom-ios-ml

CharlesWiltgen

Use when deploying ANY machine learning model on-device, converting models to CoreML, compressing models, or implementing speech-to-text. Covers CoreML conversion, MLTensor, model compression (quantization/pale...

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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