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Found 1,685 Skills
Review the latest changes and check whether they comply with the project's documented guidelines (AGENTS.md, CLAUDE.md, or equivalent). Use when reviewing local diffs, recent commits, or feature work and you need a findings-first assessment of architecture, reuse, testing, and repo-specific rules.
Ingest any raw text data, conversation logs, chat exports, or unstructured documents into the Obsidian wiki. Use this skill when the user wants to process data that isn't standard documents or Claude history — things like ChatGPT exports, Slack threads, Discord logs, meeting transcripts, journal entries, CSV data, browser bookmarks, email archives, or any raw text dump. Triggers on "ingest this data", "process these logs", "add this export to the wiki", "import my chat history from X". This is the catch-all for any text source not covered by the more specific ingest skills.
Guides you through migrating markuplint configuration from v4 to v5. Detects current versions, reviews the migration guide, interactively confirms breaking changes and new rules with the user, updates config files and tests. For Claude Code.
One-stop companion and installer for the official Tencent IMA skill (腾讯 IMA / ima.qq.com). Handles zero-config installation to Claude Code / Codex / OpenClaw via `npx skills add`, guides API key setup, detects and fixes known issues in the upstream package (including the missing-YAML-frontmatter bug in submodule SKILL.md files), and implements a personalized fan-out search strategy with priority-based knowledge base boosting. Use this skill whenever the user mentions IMA, 腾讯 IMA, ima.qq.com, ima-skill, installing or configuring ima-skill, searching across IMA knowledge bases, 知识库搜索, 笔记搜索, fan-out search with preferred KBs, or reports errors like "Skipped loading skill(s) due to invalid SKILL.md". Also trigger for any request to diagnose, repair, or personalize the behavior of an ima-skill installation. This is a wrapper layer around ima-skill — it installs and orchestrates ima-skill rather than replacing it.
Run agency-orchestrator YAML workflows directly in Claude Code / OpenClaw / Cursor — no API key required, using the current session's LLM as the execution engine. Triggered when the user provides a .yaml workflow file or requests multi-role collaboration to complete a task.
Syncs latest release content to NotebookLM and HQ Knowledge Base after version tagging. Reads CHANGELOG, CLAUDE.md, and hook README, updates notebook sources, and ingests release digest. Optionally generates podcast from updated knowledge base. Use after tagging a new version to propagate release knowledge.
Create, optimize, and iteratively refine agent prompts and system prompts. Use when asked to "improve a prompt", "optimize a system prompt", "rewrite an agent prompt", "tune prompt wording", "make this prompt more reliable", or "adapt a prompt for OpenAI, Claude, or Gemini". Handles model-specific prompt guidance, prompt markers/tags, eval design, and meta optimization loops for new and existing prompts.
Export agent data into a Starchild migration bundle. For use by ANY agent (OpenClaw, Claude Code, Cursor, etc.) to migrate into Starchild.
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.
Run the /check-phoenix-duskmoon-design Claude command workflow in Codex.
World-class design and motion. Use when designing interfaces, building front-ends, or when craft matters. Triggers on "design this", "make it beautiful", or "be french claude".
Pack entire codebases into AI-friendly files for LLM analysis. Use when consolidating code for AI review, generating codebase summaries, or preparing context for ChatGPT, Claude, or other AI tools.