Skills
99,719 packaged capabilities and playbooks for agents. Install any of them with one command.
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Use when you need to act as an Elite Software Architect (Maestro) to manage complex repositories. It enforces a "Why over How" philosophy, maintains a persistent project memory (Brain), and orchestrates specialized sub-skills through a Plan-Act-Verify lifecycle.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Creates or rewrites a README for the project consumer, using verified install commands, a runnable quickstart, and house presentation conventions. Use when asked to "write a README", "rewrite our README", or replace scaffold boilerplate. For an in-place prose audit use docs-writing; for agent instructions use agents-md
Suggest community skills based on recent activity in other plugins. Checks whether the community has built something relevant to a task and mentions it once, non-intrusively. Use when the user says "is there a community skill for this", "what else is out there", or asks for skill recommendations; also runs passively as part of other plugins' workflows.
Project status dashboard — open issues, recent commits, active branches/worktrees, memory state, and scratchpad. Use when the user asks for a status report, project overview, "what's going on", "where are we", or wants to catch up on project state without the full /catchup reconstruction
Guide users to manage Alibaba Cloud resources using the Aliyun CLI command-line tool. Covers CLI installation, credential configuration, plugin management, command construction, and error troubleshooting. Use this skill when the user wants to operate Alibaba Cloud services from the terminal — including ECS (cloud servers), Function Compute (serverless), RDS (databases), OSS (object storage), SLS (log service), VPC (networking), ESS (auto scaling), and any other Alibaba Cloud product. Also use when the user mentions "aliyun", "阿里云", "阿里云CLI", "命令行", asks about CLI plugin installation, encounters Aliyun CLI errors (InvalidAccessKeyId, SignatureDoesNotMatch, Throttling), or needs help constructing aliyun commands with correct parameter syntax.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', 'adversarial plan', 'hostile planning', 'cross-critique plan', '하이퍼플랜', '적대적 계획', '교차 비평'.
Meson build system skill for C/C++ projects. Use when setting up a Meson project, configuring build options, managing dependencies with the wrap system, cross-compiling, or integrating Meson with CI. Activates on queries about meson setup, meson compile, meson wrap, meson test, cross-file, meson.build, or migrating from CMake/Autotools to Meson.
Grassroots-first campaign design for anyone being outspent — startups vs. incumbents, NGOs vs. corporate comms, movements vs. state-backed machines, solo brands vs. big-budget competitors. Ideates awareness, launch, fundraising, mobilization, community-build, counter-narrative, referral, founder-story, and coalition campaigns. Triggers on "campaign plan", "marketing strategy", "ad budget", "should I advertise", "paid vs organic", "launch plan", "grassroots", "low budget marketing", "NGO campaign", "outspent", "competitor has bigger budget", "how do I compete without money". Also trigger on any spend asymmetry, collapsing organic reach, rising CPAs, or a trust/credibility problem — even without the word "campaign". Nudge activation when the user debates buying ads, boosting posts, or hiring influencers; they are likely about to burn money on a channel that will not persuade.
Generate type-safe API clients, TanStack Query/SWR hooks, Zod schemas, MSW mocks, Hono server handlers, MCP servers, and SolidStart actions from OpenAPI specs using Orval. Covers all clients (React/Vue/Svelte/Solid/Angular Query, Fetch, Axios), custom HTTP mutators, authentication patterns, NDJSON streaming, programmatic API, and advanced configuration.
Rust sanitizers and Miri skill for memory safety validation. Use when running AddressSanitizer or ThreadSanitizer on Rust code, interpreting sanitizer reports, using Miri to detect undefined behaviour in unsafe Rust, or validating unsafe code correctness. Activates on queries about Rust ASan, Rust TSan, Miri, RUSTFLAGS sanitize, cargo miri, unsafe Rust UB, or interpreting Rust sanitizer output
Extracts the sealed secret word from vault.bin and prints it to the console. Use when the user asks to read the secret from the vault, unlock vault.bin, or asks “what is the secret word”. The secret cannot be read by reading files; you must run the unlock.py script.
Run a bash script inside an Antithesis run at a chosen moment with `snouty runs exec`, from the terminal and without a browser. Use it for scripted forensics on a run: process and container inspection, on-disk evidence, gdb attach, and general debugging. Covers command usage, the live-session requirement, common workflows and errors, and how virtual time and perturbation limit what a debugger can see.
Migrate existing Phoenix (PX) traces, datasets, experiments, and stored evaluation results into Arize AX and verify the imported records. Use when users ask to move or copy historical Phoenix data to AX; not for adding live instrumentation or exporting AX data alone.
Autonomous multi-round research review loop. In Copilot CLI it defaults to the native complementary rubber-duck subagent with host-event model evidence; elsewhere it uses Codex, while explicit external reviewer overrides remain available. Implements fixes and re-reviews until a policy-approved positive assessment or max rounds is reached.
The foundational theory of interactive experience design - loops, motivation, feel, and the art of meaningful playUse when "game design, core loop, game feel, player motivation, game mechanics, meaningful choice, progression system, game economy, game balance, playtesting, GDD, game document, fun factor, engagement, flow state, risk reward, player agency, juice, game polish, 8 kinds of fun, bartle types, MDA framework, game-design, player-experience, core-loop, motivation, game-feel, MDA, playtesting, GDD, systems-thinking, player-psychology, engagement, flow-state" mentioned.
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
ListenHub CLI skills router. Routes to the correct skill based on user intent. Triggers on: "make a podcast", "explainer video", "read aloud", "TTS", "generate image", "generate video", "做播客", "解说视频", "朗读", "生成图片", "生成视频", "幻灯片", "slides", "音乐", "music", "generate music", "翻唱", "cover song", "pixverse", "口型", "lipsync", "对口型", "parse URL", "解析链接", "提取内容".
Uninstall a community skill that was installed via the hub. Confirms before deleting files, refuses to touch first-party plugin skills, and logs every action. Use when the user wants to fully remove a community skill ("uninstall [skill]", "remove this skill") rather than just disable it.
Jurisdiction-aware wage/hour and employment Q&A — classification, overtime, meal/rest breaks, leave, final pay — answered for the specific state/country with the controlling rule researched and cited rather than stated from memory. Use when the user asks any employment law question, or says "what's the rule in [state]", "is this exempt", "do we have to pay overtime for", or "can we classify this as".
Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user's web activity from a browser profile.
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
Use when implementing speech-to-text, audio transcription, real-time streaming STT, dictation (spoken notes turned into cleaned-up text), text-to-speech (TTS, speech synthesis), audio intelligence features, or voice AI using AssemblyAI APIs or SDKs. Use when the user mentions AssemblyAI, Blurt (AssemblyAI’s Mac dictation app), voice agents, transcription, dictation, text-to-speech, speaker diarization, PII redaction of audio, LLM Gateway for audio understanding, or applying LLMs to transcripts. Also use when building voice agents with LiveKit or Pipecat that need speech-to-text, or when working with any audio/video processing pipeline that could benefit from transcription, even if AssemblyAI is not mentioned.
Convene a structured LLM Council — five thinking-lens advisors (Red Team, First Principles, Expansionist, Outsider, Executor) plus anonymised peer review, forced debate on consensus, dual-chairman synthesis with dissent preservation, and optional Codex-powered Decision Science pass — to pressure-test high-stakes decisions. Adaptive modes (Quick/Standard/Deep) keep cost bounded; a persistent journal enables learning across runs. Mandatory triggers: /claude-council, "convene the council", "run this by the council", "I need the council", "council this", "pressure-test this", "stress-test this", "war room this", "debate this". Strong triggers: "I'm torn between X and Y", "this is a big decision", "help me think this through from multiple angles", "I need outside perspectives", "should I X or Y" (with real stakes — if binary with obvious answer, triage rejects per Step 1 rule 4). Do NOT invoke for factual questions, coding help, debugging, quick yes/no decisions, emotional support, or questions with one right answer — answer those directly. Optional suffixes: "with codex" enables Decision Science pass; "deep" forces Deep mode; "quick" forces Quick mode. Secondary invocation: /claude-council outcome <sha1> <note> records decision outcome. /claude-council meta runs journal meta-analysis.
Update the status of an in-progress international expansion project — recalculates what is now unblocked, flags anything overdue, and surfaces the next priorities. Use when work has happened since the last session and the expansion tracker needs to reflect the current state.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.