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Found 696 Skills
Use this skill to manage already-installed skills across Claude Code, Codex, Gemini, OpenCode, OpenClaw, Cursor, Copilot, and other configured agent tools by comparing skill status and linking from configured source directories such as ~/.cc-switch/skills/ and ~/.agents/skills/. Trigger it in two major cases: first, when the user wants to sync, remove, repair, or align skills or agent skills across multiple agents; second, when the user does not yet know the current skill state and wants to inspect skill differences, missing skills, per-agent skill coverage, per-skill coverage, or decide what skill changes to make next. Use this skill when the topic is cross-agent skill or agent-skill management, not for general agent comparison, general model capability questions, or creating, editing, or installing skills from GitHub.
Generate animated GIF/MP4/AVIF terminal replays from Claude Code or Codex sessions. Use this skill whenever the user wants to create a GIF, animation, video, or visual replay of a coding session — whether they say "make a gif of my session", "animate that conversation", "create a terminal recording", "share a replay", or reference agent-log-gif directly. Also trigger when users want to find, search, or browse their Claude Code or Codex sessions for visualization purposes. Can also create synthetic/fictional session GIFs from scratch for demos, docs, or tutorials — if the user says "make a demo gif showing X" or "create a fake session gif", use this.
Connect WeChat to AI agents (Claude, Codex, Gemini, Kimi, etc.) using the WeClaw bridge in Go.
Feature-complete companion for the actual CLI, an ADR-powered CLAUDE.md/AGENTS.md generator. Runs and troubleshoots actual adr-bot, status, auth, config, runners, and models. Covers all 5 runners (claude-cli, anthropic-api, openai-api, codex-cli, cursor-cli), all model patterns, all 3 output formats (claude-md, agents-md, cursor-rules), and all error types. Use when working with the actual CLI, running actual adr-bot, configuring runners or models, troubleshooting errors, or managing output files.
Installs or updates Codex CLI, Gemini CLI, and Claude Code. Use when CLI agents need installation or update.
Maintainer workflow for OpenClaw releases, prereleases, changelog release notes, and publish validation. Use when Codex needs to prepare or verify stable or beta release steps, align version naming, assemble release notes, check release auth requirements, or validate publish-time commands and artifacts.
Pull latest origin/main into the current local branch and resolve merge conflicts (aka update-branch). Use when Codex needs to sync a feature branch with origin, perform a merge-based update (not rebase), and guide conflict resolution best practices.
Run Codex, Claude Code, and Gemini CLI reviews against the current branch concurrently, deduplicate the findings, and fix only the review comments that are still valid for the current codebase.
Complete guide for integrating a new LLM backend into MassGen. Use when adding a new provider (e.g., Codex, Mistral, DeepSeek) or when auditing an existing backend for missing integration points. Covers all ~15 files that need touching.
Check AI CLI usage/quota for Claude Code, OpenAI Codex, Google Gemini CLI, and Z.AI. Use when user asks about remaining quota, usage limits, rate limits, or wants to check how much capacity is left.
Use when working with AliCloud Milvus (serverless) with PyMilvus to create collections, insert vectors, and run filtered similarity search. Optimized for Claude Code/Codex vector retrieval flows.
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.