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Found 505 Skills
Use the `orca` CLI to drive a running Orca editor — manage Orca worktrees; create, read, and run shell commands in Orca-managed terminals; and automate Orca's built-in browser (snapshot/click/fill/screenshot/tabs). Use this instead of raw `git worktree`, ad hoc shell PTYs, or Playwright whenever the task touches Orca state. Coding agents inside an Orca worktree should also use it to keep the worktree comment fresh at meaningful checkpoints. Boundary with `orchestration`: if the recipient of a terminal write is another AI agent (Claude Code, Gemini, Codex, a worker), use `orchestration` — it is the only correct way to send messages, nudges, replies, or task hand-offs to agents. orca-cli writes are for non-agent terminals (shells, build/test commands); reading or `wait`ing on any terminal — including agent terminals — stays in orca-cli.
Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts, articles, social media, or press releases - Need content that references real trends, people, and recent events - Want AI-assisted content that doesn't sound AI-generated - Creating thought leadership content in any industry Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model.
Interactive tutorial that guides engineers through building their own coding agent (agentic loop) from scratch using raw HTTP calls to an LLM API. Supports Gemini, OpenAI (and compatible endpoints), and Anthropic. Supports TypeScript, Python, Go, and Ruby. Detects progress automatically. Use when someone says "build an agent", "teach me agents", or "/build-agent".
Use when creating content that must be discoverable by AI search engines (ChatGPT, Perplexity, Gemini). Use when SEO alone isn't enough, when you need AI citations, or when optimizing for the "zero-click" future.
AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific optimization, schema markup, technical SEO, content quality (E-E-A-T), and client-ready GEO report generation. Use when user says "geo", "seo", "audit", "AI search", "AI visibility", "optimize", "citability", "llms.txt", "schema", "brand mentions", "GEO report", or any URL for analysis.
Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
Sync provider changes from cloned repositories in the providers/ folder. Use when syncing upstream changes from external provider repositories (claude-code, gemini, codex) while preserving local customizations. Includes multi-step workflow: checking for new commits via GitHub CLI, generating diffs, deep analysis, Pal MCP refactor planning, and applying changes incrementally. Never use for opencode provider (created locally, not cloned).
[QwenCloud] Recommend the best Qwen model and parameters. TRIGGER when: choosing between Qwen models, comparing Qwen model pricing, understanding Qwen model capabilities, when an execution skill needs model selection advice, or user explicitly invokes this skill by name (e.g. use qwencloud-model-selector). DO NOT TRIGGER when: non-Qwen model discussions (OpenAI, Gemini, etc.), general AI questions unrelated to Qwen.
Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which model is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers (speech-to-text aliases): "compare models", "model shootout", "which model is best".
Universal AI image generation supporting OpenAI DALL·E / gpt-image, Google Gemini Image / Imagen, Replicate (Flux / SDXL / any model), Stability AI, FAL, Ark (Seedream 4.5), Bailian (qwen-image / wanx), and SiliconFlow. Use this skill whenever the user asks to generate, create, draw, illustrate, render, or synthesize images from text prompts or reference images. Typical phrases include "draw a ...", "generate an image of ...", "画一张 ...", "给我来张图", "make a poster of ...", "create an illustration ...", or any mention of image-generation model families like DALL·E, gpt-image, Flux, SDXL, Seedream, Imagen, Gemini image, Kolors, or Wanx. Always use this skill even if the user does not name a specific model — pick a provider based on their EXTEND.md defaults or available API keys in the environment. Do NOT use this skill when the user explicitly mentions 即梦 / Dreamina / Jimeng — those go to happy-dreamina instead.