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Found 480 Skills
Rewrite Python docs and docstrings from source code. Use when Codex needs to refresh the docs.
Premium UI design engineering skill for creating, redesigning, polishing, and judging product-specific interfaces with senior-level craft. Use when Codex works on frontend design, UX/UI, design systems, dashboards, SaaS apps, landing pages, commerce, portfolios, visual polish, interaction quality, or wants output in the spirit of Vercel, Linear, Raycast, Awwwards, and high-end product teams. Composes with no-slop as the anti-generic gate.
Cross-platform CLI tool for managing Claude Code, Codex, Gemini, OpenCode & OpenClaw providers, MCP servers, prompts, skills, and proxies.
Reusable CSS motion library for Animation Master. Use when Codex needs to add, copy, adapt, or package local `.t-*` CSS animation effects for element motion, UI transitions, text motion, number rolling, badges, menus, modals, page transitions, hover states, or one-click CSS snippets.
Pre-consultation diagnostic questionnaire for clients building websites with AI tools (Claude, Codex, Cursor, Bolt, v0, etc.) who have concerns about quality, design, or maintainability. Collects structured answers about their project, tools, pain points, and goals, then generates a consultation brief. Use when preparing for a website review consultation, when a client asks for a site audit, or when someone says their AI-built site has problems. Supports Russian and English — asks the client to choose language first.
Run a spec-driven agent loop where coding tasks live as markdown specs that move through inbox → active → archive, get implemented by Claude Code or Codex, and pass a review gate before they count as done. Use when the user mentions "loop factory", a "spec-driven loop", an "agent factory", wants repeatable/reviewable agent work, or when a repo has a factory/specs/inbox or factory/specs/active directory. Also covers installing and scaffolding the loop-factory CLI into a project.
Consult an advisory council of three AI personas — Cato (skeptic), Ada (optimist), Marcus (pragmatist) — backed by different frontier LLM agents (Gemini, Claude, Codex). Each persona runs as a separate agent process with full repo context and returns independent feedback. Use when the user says "/council", asks for a second opinion, wants feedback on code changes, needs a premortem, wants to pressure-test a decision, or asks "what do you think about this approach?" Claude may also proactively suggest consulting the council before major architectural decisions, risky deploys, or ambiguous trade-offs (but should ask for user approval first).
12 production-ready regulatory affairs and quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO compliance, risk management (ISO 14971), CAPA, document control, and internal auditing. Python tools included (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
Use this skill whenever a user wants to run, install, configure, or understand open-ralph-wiggum (ralph). This skill can be used by any AI assistant or IDE agent (GitHub Copilot, Claude Code, Cursor, Windsurf, etc.). Triggers on: "ralph", "ralph wiggum", "agentic loop", "iterative AI loop", "autonomous coding loop", "how to install ralph", "how to use ralph with Claude Code / Codex / Copilot / OpenCode", "ralph --agent", "ralph --tasks", "ralph --status", "--max-iterations", "--rotation", "how do I run ralph in VS Code / Cursor / JetBrains / Neovim", or any question about looping an AI coding agent until a task is done. Even if the user doesn't say "ralph" explicitly — if they want to run an AI agent in a loop until a promise tag appears in its output, use this skill.
Harvest coding-agent session transcripts already on disk (Claude Code, Codex, OpenCode, Cursor, Pi) and extract durable knowledge — topics, people, facts, events, quotes — into whatever persistent memory the agent can reach. Cursor-tracked, budgeted, read-only on sources. Use when asked to collect/import/mine session history into memory, build memory from past sessions, or as a scheduled task. Composes with memory-gardener, which tends what this skill plants.
Run the trigger evaluation pipeline — classify, analyze, and optionally compare against a baseline. Only run when explicitly asked — evals are expensive.
Analyze a task, pick the right fleet type, and generate a ready-to-launch fleet (fleet.json + prompt.md files). Discovers available fleet skills dynamically. Use when the user wants to run work in parallel, asks to "plan a fleet", or says "fleet-plan".