Browse Skills

World-class game UI design expertise combining the clarity of Nintendo's UI philosophy, the immersive diegetic interfaces of Dead Space and Metroid Prime, and the competitive readability principles from esports titles. Game UI is the invisible bridge between player intent and game response. Great game UI serves the player without breaking immersion. It communicates critical information at a glance during intense action, guides new players without patronizing veterans, and adapts gracefully from 4K monitors to handheld screens and from keyboard to touch to controller. The best game UI designers understand that every pixel of screen space is sacred - borrowed from the game world itself. Use when "game ui, game interface, hud design, heads up display, game menu, inventory ui, health bar, stamina bar, game hud, minimap, crosshair, reticle, button prompt, controller ui, gamepad navigation, diegetic interface, in-world ui, quest tracker, damage numbers, cooldown indicator, radial menu, game tooltip, game-ui, hud, game-interface, game-menu, controller-ui, diegetic, game-design, accessibility, console, mobile-games" mentioned.

Edit PDFs with natural-language instructions using the nano-pdf CLI.

Create professional cinematic scripts for AI video generation with character consistency and cinematography knowledge. Use when the user wants to write a cinematic script, create story contexts with characters, generate image prompts for AI video tools (Midjourney, Sora, Veo), or needs cinematography guidance (camera angles, lighting, color grading). Also use for character consistency sheets, voice profiles, anachronism detection, and saving scripts to Google Drive.

Use when editing videos with DashScope HappyHorse 1.0 video editing model (happyhorse-1.0-video-edit). Use when implementing instruction-based video editing such as style transfer or local replacement, optionally guided by 0-5 reference images, via the video-synthesis async API on Alibaba Cloud Model Studio.

Use when setting up an email inbox for an AI agent (Moltbot, Clawdbot, or similar) - configuring inbound email, webhooks, tunneling for local development, and implementing security measures to prevent prompt injection attacks.

OpenClaw skill discovery, security vetting & install. Searches 3000+ curated skills from ClawHub registry and awesome-openclaw-skills catalog. Scores credibility, detects prompt injection & malicious patterns, manages installations. Quick-checks GitHub for new skills.

Autonomous self-evolution skill: grants the agent full authority to modify its own configuration, skills, prompts, AGENTS.md, SOUL.md, memory files, and any workspace file WITHOUT asking for user confirmation. The agent should proactively identify weaknesses, fix them, write new skills, and continuously improve itself.

Your data has answers. CellCog asks the right questions. #1 on DeepResearch Bench (Feb 2026) + frontier coding agent — upload messy CSVs with minimal prompting and get structured insights back: charts, dashboards, statistical reports, and clean data. Full Python access for data cleaning, exploratory analysis, visualization, hypothesis testing, ML model evaluation, and dataset profiling. Analyzes everything, presents it beautifully.

Enterprise MCP (Model Context Protocol) server development using FastMCP 2.0 with production-grade tools, resources, prompts, and intelligent agent-first design. Use when building MCP servers, integrating with LLMs, creating agent tools, implementing RAG systems, or developing protocol-based AI integration solutions.

Generate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDK

Generate a complete Rust Model Context Protocol server project with tools, prompts, resources, and tests using the official rmcp SDK

Multi-step reasoning patterns and frameworks for systematic problem solving. Activate for Chain-of-Thought, Tree-of-Thought, hypothesis-driven debugging, and structured analytical approaches that leverage extended thinking.

Run a GEPA learning cycle via `metaharness learn` (upstream ADR-235, [email protected]) — optimizes a harness genome against a SWE-bench-style slice manifest. $0 dry-run by default; `--run` is the explicit spend opt-in. Requires a metaharness repo checkout (`--repo` or $METAHARNESS_REPO) — without one it reports `checkout-required` with clone instructions. Degrades gracefully when metaharness is absent.

Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.

Rapidly creates atomic, focused skills optimized with evidence-based prompting, specialist agents, and systematic testing. Each micro-skill does one thing exceptionally well using self-consistency, program-of-thought, and plan-and-solve patterns. Enhanced with agent-creator principles and functionality-audit validation. Perfect for building composable workflow components.

Creates new OpenClaw skills following best practices. Interactive workflow for use case definition, frontmatter generation, instruction writing, and validation. Use when user says "create skill", "new skill", "make a skill", or needs to build a skill from scratch.

Work with Obsidian vaults as a knowledge base. Features: fuzzy/phonetic search across all notes, auto-folder detection for new notes, create/read/edit notes with frontmatter, manage tags and wikilinks. Use when: querying knowledge base, saving notes/documents, editing existing notes by user instructions.

Audit a design against Dieter Rams' ten "Good design is..." principles, then hand off a /make-plan prompt for one of three outcomes — new design, refine design, or redesign. Use when the user says "audit this design", "design review", "check this UI against Rams", "is this UI good", "critique this design", "design audit", or asks for a critique that should lead to a plan.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Creates production-ready MCP servers with tools, resources, and prompts using TypeScript SDK or Python FastMCP. Use when building MCP integrations for Claude or LLM applications.