Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Full-cycle literature workflow skill. Prerequisite: merge and deduplicate bibliographic records exported from multiple sources (see references/multi-source-retrieval.md). Four modes: (1) search; (2) reading and review; (3) insert \cite{} in LaTeX; (4) generate BibTeX. See also non-zotero-bibliography.md (EndNote/Word, etc.). For systematic review screening and PRISMA, see the systematic-review-lite skill
Use when validating subjective quality criteria that cannot be deterministically tested — applies LLM-based evaluation with structured rubrics for tone, aesthetics, UX feel, documentation quality, and code readability. Triggers: documentation quality check, error message tone review, UX copy evaluation, code readability assessment, design aesthetic review.
Full-dimension log analysis skill. Automatically identifies log types (Java application / MySQL Binlog / Nginx / Trace / alerting), extracts key entities (IP, thread_id, trace_id, user, table names, etc.), and performs root cause localization, alert analysis, and anomaly insights. Supports 100M+ large files. Trigger words: analyze logs, log troubleshooting, root cause localization, alert analysis, anomaly analysis.
Diagnoses macOS system-level slowness, heat and fleet-wide timeouts: high load average, leaked per-session child processes (MCP servers, helpers), fork storms, busy loops. Use when the Mac feels slow or hot, fans spin up, or everything times out at once (电脑发烫/卡顿/负载高/全部超时). Not for single-app bugs, network slowness (use tunnel-doctor), launchd watchdog design (use macos-watchdog), or disk-full (use macos-cleaner).
Use when managing a manuscript project over time. Scaffolds the project structure, tracks writing progress across phases, maintains project memory files, and generates submission checklists and backwards timelines (commands init, status, sync-memory, checklist, timeline).
Comprehensive market environment analysis and reporting tool. Analyzes global markets including US, European, Asian markets, forex, commodities, and economic indicators. Provides risk-on/risk-off assessment, sector analysis, and technical indicator interpretation. Triggers on keywords like market analysis, market environment, global markets, trading environment, market conditions, investment climate, market sentiment, forex analysis, stock market analysis, 相場環境, 市場分析, マーケット状況, 投資環境.
When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' 'ideas to grow,' 'what else can I try,' 'I don't know how to market this,' 'brainstorm marketing,' or 'what marketing should I do.' Use this as a starting point whenever someone is stuck or looking for inspiration on how to grow. For specific channel execution, see the relevant skill (paid-ads, social-content, email-sequence, etc.).
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use when user needs to understand, analyze, or describe image content. Do NOT use Read tool to read images — use this skill instead. Supports local file path input. 触发词：图片理解, 图片分析, 图片描述, 识别图片, 看图, 图片识别, image understanding, describe image, analyze image, 图片内容, 看看这张图, 这张图是什么, 图中有什么
Use when the user needs mobile app design and development patterns for React Native, Flutter, or SwiftUI — including platform HIG compliance, gestures, and offline-first architecture. Triggers: user says "mobile", "iOS", "Android", "React Native", "Flutter", "SwiftUI", "app design", "mobile navigation", "touch targets", "offline-first".
Comprehensive SEO audit skill for Next.js and HTML pages. Covers on-page optimisation, JSON-LD schema validation, meta tags, Open Graph, semantic HTML, site speed, mobile responsiveness, and backlink analysis. Use when a user asks to audit, optimise, or fix SEO issues on a webpage or website.
NTU EEE MSc dissertation LaTeX expert. Clones template, sets up local compilation with live preview, and guides academic writing. Use when creating an NTU dissertation project, editing .tex/.bib files, writing thesis chapters, asking about NTU format, or needing LaTeX compilation help.
Combined OpenHarmony XTS build and run commands. Completes the build and run of an XTS test project in one stop. Use this Skill when the user needs to run the full XTS test flow: (1) build the XTS test project to generate a HAP file, (2) run the XTS tests and display the results. Supports passing the --package and --api parameters through to the run stage.
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions “onboarding flow,” “activation rate,” “user activation,” “first-run experience,” “empty states,” “onboarding checklist,” “aha moment,” “new user experience,” “users aren't activating,” “nobody completes setup,” “low activation rate,” “users sign up but don't use the product,” “time to value,” or “first session experience.” Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
Eight-stage PDCA problem-solving workflow that persists analysis, proposal, design review, plan, execution, and verification into OpenSpec artifacts (openspec/changes/<name>/, archived into openspec/specs/) instead of leaving them only in chat context. Use for feature work, bug fixes, refactors, and complex engineering tasks that need long-term behavioral-contract traceability, team review, or auditability. Do NOT use for a quick one-off edit with no traceability need — use solve-workflow instead. Triggers：「opsx解决」「OpenSpec解决」「规范化解决」「创建OpenSpec变更」「创建opsx变更」「用OpenSpec分析」「用OpenSpec修复」「opsx自动解决」「OpenSpec自动解决」「opsx-solve」「opsx-solve-workflow」；「ai-proxy 模式」「AI 代理模式」「切换 ai-proxy」 / opsx solve, OpenSpec solve workflow, create an OpenSpec change, ai-proxy mode, switch to ai-proxy.
Pachca — managing chats, channels and conversations. Use this skill when the user wants to create a channel, create a conversation, list or archive chats, add or remove participants, change participant roles, export chat history, or check chat settings. NOT for sending messages or replying in a thread. Use when: create channel, create conversation, create chat, add participant, remove participant, archive chat, participant roles, export messages, list chats, all workspace chats, channels. NOT for: send message, reply in thread, upload file, → pachca-messages, → pachca-users, full-text search of chats by name → pachca-search.
Поиск, пересказ и напоминания в Пачке: какой поиск что охватывает, тред целиком, разбор проблемы или замечаний из треда, дайджест за период, поручения в напоминания, напоминание на время себе или коллеге, свои напоминания и «Важное», кто в теге или чате. Когда: «найди, где обсуждали», «кто писал про», «где меня упоминали», «найди чат», «найди сотрудника», «перескажи тред», «что поправить по треду», «в чём проблема по треду», «что было в канале за неделю», «дайджест», «какие решения приняли», «поставь задачи по итогам», «напомни мне завтра в 9:00», «мои напоминания», «что у меня в важном», «кто в теге», «кто в чате», "find where we discussed", "summarize this thread", "what feedback is in the thread", "channel digest", "remind me tomorrow at 9". Not for: posting, pinning, reacting to or editing a message, finding it first included, or one sent later at a set time → pachca-messaging; changing employees, tags or chat members → pachca-admin; a bot that answers in threads → pachca-ai-agent; scripts → pachca-api.
Build a scroll-driven cinematic landing page from a short video. The user provides a 5–15 second video (often AI-generated); this skill extracts every frame at HD JPEG quality, then produces a single-hero HTML page where the user's scroll gesture scrubs the frames in place (the page itself never scrolls) and 5 dramatic text overlays crossfade in/out — Google Anton headlines, Caveat handwritten accents, locked body, virtual scroll. Use this skill whenever the user wants to "turn this video into a landing page", "make a scroll-scrub landing page", "build a parallax hero from this clip", "add a new landing page to the parasites showcase", "do the same as github/lion/hope for this new video", or any variant that pairs a short clip with dramatic scroll-triggered storytelling. Trigger even if the user only says "use my video for a landing page" — that is this skill.
Configure and interpret the Phoenix plugin for Harbor agent evaluations. Use when adding `arize-phoenix` to Harbor jobs, choosing ATIF tracing, mapping Harbor tasks and rewards to Phoenix experiments, comparing agents or models, resuming jobs, or troubleshooting Harbor records in Phoenix.
Bring the user's own clips, photos or audio into Picsart as hosted URLs, through the gen-ai MCP's upload widget or, where a shell can read the file, a direct upload. Use when a Picsart tool needs a URL and the media is on the user's machine or in a chat attachment
Use when a PinMe Cloudflare Worker needs R2 object storage, including secure file or image upload, streaming download, metadata lookup, deletion, listing, Range requests, or R2+D1 coordination. Guides AI to use PinMe's automatically injected env.R2 binding without R2 credentials or manual Wrangler configuration.
Autonomous build-phase orchestrator with 8-stage per-slice pipeline (decompose, slice readiness review, implement via TDD pairs, three-stage code review, address feedback, mutation testing, push/CI, merge/flag). Manages slice queue (walking skeleton first, dependency ordering), dispatches TDD pairs with capability detection, enforces 5 binary quality gates with 3-cycle rework budgets and human escalation, maintains audit trail, and respects strict controller boundaries (never writes code, delegates all creative work). Supports three autonomy levels (conservative/standard/full). Use when running factory mode, orchestrating build phases, managing slice queues, or coordinating TDD pairs with review gates. Triggers on: "run the pipeline", "factory mode", "build phase", "slice queue", "quality gates", "autonomous build". NOT for: individual TDD (use tdd), standalone code reviews (use code-review), CI-only workflows (use ci-integration).
Structured planning workflow for any coding task. Use at the start of every new feature, bug fix, refactor, or implementation request. Analyzes the project, asks up to 5 clarifying questions, creates a TODO.md, gets user approval, then executes task by task. Never writes code before a plan is approved.
Use when the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions “exit intent,” “popup conversions,” “modal optimization,” “lead capture popup,” “email popup,” “announcement banner,” “overlay,” “collect emails with a popup,” “exit popup,” “scroll trigger,” “sticky bar,” or “notification bar.” Use this for any overlay or interrupt-style conversion element. For forms outside of popups, see form-cro. For general page conversion optimization, see page-cro.
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Use after editing or writing any Datex Studio component file — invoked by every creator skill's closer ("After your edit, invoke post-edit-verification"). Runs the verification stack cheapest-first: Edit/Write tool succeeded → JSON parses → description is non-null, non-empty, ≤100 chars (platform limit) → grep for obvious typos. Escalates to component-validator subagent for non-trivial edits. Replaces Mitch's PostToolUse validate-component.py hook with a skill-based pattern. Triggers: invoked by every component-creator's closer; rarely invoked directly by users.
Official reference guide for the PPIO platform, covering the LLM API (OpenAI-compatible), Agent sandboxes, GPU (instances and serverless), integrations, authentication, pricing, rate limiting, and troubleshooting. Applies to questions such as "How do I integrate PPIO into a specific use case?" and common issues like failed PPIO requests.
STEP 2 of the PPTX-from-layouts pipeline. Write a slide deck in markdown using the [HINT: layout_name] system so each slide targets a real template layout, then lint it before rendering. Use when the user wants to "draft slides", "write a deck outline", "author presentation markdown", "add layout hints", or has a layout catalog from Step 1 and needs to turn content into slides. Pairs with pptx-profile (Step 1) and pptx-from-layouts (Step 3).
Help writing PRDs, analyzing feature requirements, and planning roadmaps. Use when writing a PRD, analyzing feature requests, planning a roadmap, or when you need structured product thinking. Triggers on "PRD", "產品規格", "feature request", "roadmap", "功能分析".
Programmatic Power BI development with PBIR, PBIP, TMDL, TOM, and fabric-cicd. PROACTIVELY activate for: (1) creating Power BI reports programmatically (PBIR enhanced report format), (2) PBIR vs PBIR-Legacy selection (2026 default), (3) PBIP developer mode and Power BI project files, (4) Tabular Object Model (TOM) / .NET SDK scripting, (5) Tabular Editor scripting (C# scripts, advanced scripting), (6) pbi-tools workflows, (7) fabric-cicd Python deployments (FabricWorkspace, publish_all_items), (8) Fabric CLI (fab deploy), (9) Semantic Link / sempy / semantic-link-labs, (10) generating PBIX programmatically, (11) parameter.yml for environment-specific deployments, (12) ALM Toolkit. Provides: PBIR/PBIP project templates, fabric-cicd deploy.py, Tabular Editor scripting recipes, parameter.yml patterns, and end-to-end programmatic workflows.
Maintains project context and progress tracking across Claude sessions. Use at session start to load context, on session end to save progress. Triggers: load project context, save context, end session, what was I working on, switch to project, done for today.
Use when running project-wide lint across a Datex Studio codebase (or a scope subset) — checks 5 categories of cross-component issues that per-file validation misses: (1) description-rule conformance across all component files, (2) schema-code alignment between declared `inParams`/`outParams` and the embedded TypeScript that consumes them, (3) cross-component `objectType` reference resolution, (4) OData query pre-flight against connection schemas, (5) result-shape sync between a datasource's query options and its declared `outParams`. Triggers: "validate the project", "run cross-component validation checks", "lint the codebase", "find broken type references", "find OData pre-flight failures", "check the project before merge". For single-file audits use `component-validator` instead.
Generate a PR_MESSAGE.md file from session context using GitHub CLI. Detects related issues via branch-keyword search, writes a structured PR description with commit subject, summary, test plan, and changelog. Validates with commitlint and markdownlint. Use when preparing a pull request on GitHub.
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.