Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Master the art of calls-to-action that convert. Direct CTAs, transitional CTAs, button copy, and microcopy that turns readers into customers. Use when: Writing button text for landing pages and emails; Creating CTAs for different stages of awareness; Designing click-worthy microcopy; A/B testing CTA variations; Building email sequences with graduated CTAs
Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks you to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.
AI-native video editor for any agent. Use when the user asks to edit, trim, splice, caption, zoom into, add a title card, transition between, remove silence from, chroma-key, stabilize, or render video files. Wraps FFmpeg in 19 deterministic tools and a session log; runs locally; no generative AI.
Generate and analyze DNA sequences using NVIDIA's Evo 2 BioNeMo NIM microservice. Use for Evo2/Evo 2, DNA generation, genomic sequence generation, hosted generation, local Docker deployment, local forward passes, layer outputs, logits, sampled probabilities, and BioNeMo NIM workflows
Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey completeness, then summarizes the pre-error context. Replaces blind session picking from potentially hundreds of linked recordings
Expert blueprint for Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.
Fully automated, one-stop HAP app builder. Starts with business solution design (Plan), then automatically builds it (Build) after confirmation. If a plan already exists, continue or resume the build with one click. Triggered when the user enters /hap-builder or describes their system requirements in conversation (e.g., “Help me build a customer management app”).
Meta XR Mixed Reality Utility Kit (MRUK) (com.meta.xr.mrutilitykit) for Unity XR development. Use when working with Scene API data (rooms, walls, floors, furniture), spawning prefabs on scene anchors, placing virtual objects in the real world, world locking to prevent anchor drift, raycasting against room geometry, generating NavMesh from scene data, environment depth raycasting for instant placement without scanning, Passthrough Camera Access (PCA), trackable detection (keyboards, QR codes), destructible scene meshes, space maps, room sharing for multiplayer, or any MR scene-aware feature
Analyzes the user's business problem and recommends the right backend integration approach — Web API, AI Web API (generative summaries / grounded search), Server Logic, Cloud Flows, or a combination — for a Power Pages site, then routes to the appropriate specialized skill. Use when the user wants to add backend integration, connect to data, add AI summaries, or needs help deciding which backend approach to use.
An AI text generation tool that uses large language models to generate text from prompts, with combined image, video, and text understanding. Choose between GEM_3_FLASH (fast) and GEM_3_1_PRO (high-quality complex analysis). Triggers when the user says “AI生文,” “AI写作,” “文本生成,” “帮我写一段,” “text generation,” “generate text,” “用AI写,” “AI分析图片内容,” “图片识别,” or “视频分析”
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
Use the `nb` CLI for all Jupyter notebook (`.ipynb`) operations, including reading, inspecting, creating, editing cells, deleting cells, clearing outputs, searching, executing, and working with connected JupyterLab sessions or remote kernel gateways. Required when an agent needs deterministic notebook manipulation without directly reading or writing raw notebook JSON.
(NS) Harness boot + brownfield prepare. Triggers: /ns-harness, prepare this repo, harness prepare, generate architecture rules, architecture-rules.md, write AGENTS.md, reverse-engineer codebase, engenharia reversa, brownfield map, bootstrap brownfield, ns-harness-prepare, ns-architecture-rules, ns-agent-generator, ns-codebase-reverse-spec, ns-bootstrap-brownfield. Do NOT: coding, SDD, GitLab.
Write structured, opinionated PRDs that engineers actually read. Use when asked to write a PRD, product spec, feature requirements, or product requirements document. Creates concise, evidence-backed specs with clear scope boundaries and measurable success criteria.
Manage a stateful, run-directory-based proof project: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.
Run ProteinMPNN inverse folding via NVIDIA NIM to design protein sequences for a target backbone. Sends user-provided PDB files and design parameters to NVIDIA's hosted API, authenticated with an environment API key, or to a user-selected local NIM. Use for sequence design, backbone redesign, fixed chains and residues, omit_AAs, sampling temperature, soluble model, local Docker, and multi-FASTA output.
Orders scheduler. Reads .noodle/mise.json and writes .noodle/orders-next.json. Schedules work orders based on backlog state, plan phases, session history, and task type schedules. Triggers when orders are empty, after backlog changes, when the loop re-evaluates, or when /schedule is invoked.
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
Comprehensive web quality audit covering performance, accessibility, SEO, and best practices in a single review. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website" across multiple areas at once. Orchestrates specialized skills for depth. Do NOT use for single-area audits — prefer core-web-vitals, web-accessibility, seo, or web-best-practices for focused work.
Fast, zero-friction capture of technical findings from the current conversation to the wiki's _raw/ staging area. Use this skill when the user says “/wiki-quick-chat-capture,” “quick capture,” “capture this finding,” “save this bug fix,” “capture this gotcha,” “drop this to raw,” “quick save to wiki,” or wants to capture a non-obvious discovery mid-session without a full wiki-ingest run. Writes one _raw/ file per topic cluster in under 60 seconds — no subagents, no QMD updates, no manifest writes. Run /wiki-ingest or /data-ingest later to promote raw files to proper wiki pages.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guide the user through the full flow: install dlt, choose a SaaS source, set up credentials, run the data pipeline into DuckDB, then automatically generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Install bundled ZenMux Codex APP pets from this skill into the user's Codex pets directory. Use when the user asks to install, copy, enable, set up, or use ZenMux pets, Codex pets, Codex APP pets, pet.json pet folders, or the bundled pets under zenmux-codex-pets/pets. Trigger on "install ZenMux pets", "Codex pets", "安装 ZenMux pets", "安装 Codex 宠物", "复制 pets 到 .codex/pets".
Manage Linux systems, including systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
Step-by-step guide for openclaw users to build, deploy, and monetise an AI agent with aixyz. Covers everything from zero: installing Bun, scaffolding an agent, choosing a deployment option, getting a crypto wallet, funding it for on-chain registration, and marketing your agent once it is live.
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.