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Found 9,776 Skills
Automatically collect hot topics in the AI field or complete AI technical article writing in the writing style of 'Second Brother' according to specified topics. It focuses on actual tests of AI Coding tools (Claude Code, Qoder, Cursor, TRAE, etc.), engineering implementation of large models (SpringAI, LangChain, RAG, etc.), AI Agent and workflow orchestration, evaluation of domestic large models (GLM, Tongyi Qianwen, DeepSeek, MiniMax, Kimi, etc.), and evaluation of various AI tools and Agent tools. Trigger keywords: write an AI article, AI technical article, large model evaluation, AI tool actual test, GLM, Claude Code, Qoder, Cursor, TRAE, SpringAI, RAG, Agent, workflow, domestic large model, collect AI hot topics, AI topic, etc.
Use the xurl CLI to resolve unified agents:// URIs (and legacy provider URIs) for Amp, Codex, Claude, Gemini, Pi, and OpenCode thread reading workflows.
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
Assist Claude in running PyWGCNA through omicverse—preprocessing expression matrices, constructing co-expression modules, visualising eigengenes, and extracting hub genes.
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.
Bridge plugin capabilities (commands, skills, agents, hooks, MCP) to specific agent environments (Claude Code, GitHub Copilot, Gemini, Antigravity). Use this skill when converting or installing a plugin to a target runtime.
Adds an "AI Summary Request" footer component with clickable AI platform icons (ChatGPT, Claude, Gemini, Grok, Perplexity) that pre-populate prompts for users to get AI summaries of the website. Optionally creates an llms.txt file for enhanced AI discoverability. Use when users want to add AI platform integration buttons or make their website AI-friendly.
Boîte à outils complète pour la création, l'édition et l'analyse de documents avec support du suivi de modifications, commentaires, préservation du formatage et extraction de texte. Quand Claude doit travailler avec des documents professionnels (.docx) pour : (1) Créer de nouveaux documents, (2) Modifier ou éditer du contenu, (3) Travailler avec le suivi de modifications, (4) Ajouter des commentaires, ou toute autre tâche documentaire.
Generate CLAUDE.md and AGENTS.md by exploring the codebase
Analyzes and compares existing skills from any source (skills.sh, GitHub, Claude marketplace, or local files) against a target skill or requirement. Fetches skill content, evaluates it across 10 dimensions, produces a structured comparison table, identifies gaps, and recommends whether to adopt, adapt, or build from scratch. Trigger when: analyze this skill, compare skills, is this skill good enough, what does this skill do, skill evaluation, should I use this skill, skill gap analysis, paste a skills.sh URL, GitHub skill URL, or upload a SKILL.md file for review.
Install, initialize, verify, and troubleshoot RTK (Rust Token Killer) for AI coding agents. Use when you need to reduce shell-command token output, confirm that the correct `rtk` binary is installed, choose between Homebrew, install.sh, or Cargo installation, wire `rtk init` for Claude Code, Codex, Gemini CLI, Cursor, Copilot, Windsurf, Cline, or OpenCode, or use compact wrappers such as `rtk git status`, `rtk read`, `rtk grep`, `rtk test`, `rtk lint`, and `rtk gain`. Triggers on: rtk, rust token killer, token saver cli, rtk init, rtk gain, codex rtk, gemini rtk, opencode rtk, claude hook token reduction.
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.