Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
Search the vault using QMD semantic search. Use PROACTIVELY before reading files. Preference order: (1) MCP tools — mcp__qmd__query, mcp__qmd__get, mcp__qmd__multi_get, mcp__qmd__status — if they appear in your tool menu, use them first; (2) CLI `qmd --index <name> ...` as fallback; (3) Grep/Glob only when QMD is not installed. Trigger proactively for past decisions, incidents, people, meetings, architecture, patterns, or any vault content — and after creating/editing notes to check for duplicates and related content.
Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a tight current-state brief. Use for “recall my work on X”, “catch me up”, “what have I been working on”, “where did I leave off”, before starting or resuming work.
Plans backward from a fixed goal or deadline to the present, identifying required milestones, dependencies, critical path, and feasibility constraints to transform aspirational targets into actionable sequenced plans. Use when planning with fixed deadlines, working backward from future goals, mapping critical path, or when user mentions "backcast", "work backward from", "reverse planning", "we need to launch by", "target date is", or "what needs to happen to reach".
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.
Web search and content extraction using ddgs (multi-engine metasearch). No API keys required. Use when: searching documentation, facts, current information, news, fetching web content. Triggers: search the web, look up, find information, web search, news search, fetch page.
Use when writing communication aimed at colleagues rather than users or customers — 3P updates (Progress/Plans/Problems), status reports, leadership and exec updates, company newsletters, FAQ answers, project updates, incident reports, launch announcements, or policy and reorganization notes. Triggers include "write an update for leadership", "draft the weekly status", "announce this to the company", "write the incident writeup".
Comprehensive qualitative research methods assistant supporting thematic analysis (Braun & Clarke), grounded theory (Strauss & Corbin; Charmaz), interpretative phenomenological analysis (IPA), content analysis, narrative inquiry, ethnography, case study methodology (Yin), coding techniques (open/axial/selective), NVivo-style workflows with Python alternatives, trustworthiness criteria (Lincoln & Guba), reflexivity, and member checking. Use when designing or analyzing qualitative research — thematic analysis, grounded theory, coding data, phenomenology, IPA, ethnography, case study, narrative inquiry, content analysis, qualitative coding, NVivo, trustworthiness, member checking, reflexivity, interview analysis, or focus group analysis. Part of the AlterLab Academic Skills suite.
Manage Apple Notes on macOS — list, search, read, create, append, move, delete, and export notes, and manage folders. Use when the user mentions Apple Notes / 备忘录, "add a note", "my notes", searching their notes, organizing folders, or exporting a note to Markdown/HTML. macOS-only; runs locally against Notes.app — no cloud API, no token.
Fetch and analyze an arXiv paper via tiered fallback (markdown -> arXiv HTML -> ar5iv -> PDF). Rate-limited for arxiv2md (28 req/min, deterministic). Produces a structured summary with citation, problem, key claims, method, results, limitations. Use when the user says "analyze arxiv paper", "summarize arxiv", "read paper", "what does this paper say", or provides an arXiv ID/URL to analyze.
From logic to speech: chains the three independent skills barry-logic-training → barry-speech-training → barry-translation-training to produce a complete English speech in one go. The orchestrator only handles the hand-offs and mode selection; the specific logic of each stage is defined by the corresponding independent skill. Two tracks: standard track (step-by-step confirmation) and fast track (produce the finished piece in one go). Triggers: 逻辑到演讲, 从逻辑到演讲, logic to speech, 帮我梳理逻辑然后准备演讲, 梳理加演讲, 整理成演讲.
Standalone logical thinking training for working professionals. Two modes: exploration mode (not yet clear, need to start from finding the real problem and build up to a pyramid) and structuring mode (content already exists, just needs reorganising into a pyramid structure). The AI acts as a Socratic coach, using follow-up questions to guide students to complete their own thinking. Triggers: 逻辑思维训练, 逻辑训练, 练逻辑, 搭金字塔, logic training, 帮我梳理一下.
Design a Barry learner's training plan + automatically generate a dedicated daily training skill. Reads learner profile Section 1+2+3 + the Four-Strands training method toolbox, designs the Section 4 training plan, and after learner authorization automatically installs it to <current AI agent skills directory>/barry-daily-<nickname>/, copying the Quiz web code to ~/.barry-english/quiz-web/. **Prerequisite: barry-profile + barry-assessment must already be completed**. 10-15 minutes. Trigger words: 定制方案、出方案、训练方案、生成训练 Skill、barry solution.
Standalone public speaking training for working professionals. Core differentiator: in-depth audience analysis drives the structure design. Two modes: coaching mode (build from scratch) and fast mode (produce a framework directly from existing material, then fine-tune). Triggers: 演讲训练, 公众演讲训练, 练演讲, speech training.
Download Bilibili video subtitles, chunk them for LLM processing, and generate high-quality summaries. Use when the user provides a Bilibili BV number or URL and wants a summary, key points, or a detailed breakdown of the video content.
Track upcoming catalysts for A-share coverage universe — earnings dates, regulatory announcements, sector conferences, product launches, and policy events relevant to Chinese equities. Adapted from the original catalyst-calendar skill for A-share market conventions. Triggers on "A股催化剂日历", "事件日历", "财报日历", "earnings calendar A-share", "upcoming catalysts China", or "what's coming up for [company]".
Deep research skill — activates when the user needs systematic investigation of any topic. Runs multiple rounds of search, cross-verifies multiple sources, integrates information in a structured way, and finally outputs a research report with cited sources. Applies to: in-depth understanding of a topic, multi-dimensional comparative analysis, comprehensive research, trend assessment and similar scenarios.
Use when the user needs professional email drafting, tone adjustment, template creation, or communication strategy for business correspondence. Trigger conditions: draft professional email, adjust email tone, create email template, write cold outreach, compose follow-up, draft escalation email, write apology email, craft meeting request, compose status update, plan email communication strategy.
Git-based engineering retrospective analyzing commits, PRs, and velocity over configurable windows with monorepo path scoping. Triggers on: "retrospective", "sprint retro", "weekly review", "what did we ship", "engineering retro", "dev summary", "commit analysis".
Build and debug Fabric.so HTTP or TypeScript SDK integrations for resources, search, uploads, and developer memory bases. Use for explicit Fabric.so API work; use fabric-cli for terminal operations. Not Microsoft Fabric, Python Fabric SSH, Fabric.js, or the unrelated Fabric prompt framework.
Use for lateral thinking, or when ideas feel stuck or incremental: "we've tried everything", "need a surprising angle", "break the pattern", "give me a wild idea that could work". Uses provocations and reframes. Skip for rule lookups or strict logical proofs.
Query official Microsoft documentation for concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP by default, with Context7 and Aspire MCP for content outside learn.microsoft.com.
Search and read documents, repos, URLs, and other resources stored in OpenViking under viking://resources/. Use whenever the user asks about docs, specs, codebases, papers, or notes that were added to OpenViking (“check the docs”, “what does our design doc say”, “find it in OpenViking”), or when a task needs reference material this session does not have. Covers picking between find, grep, glob, and list, and drilling from a hit down to the exact file
Paper interpretation assistant. Use when the user sends an arXiv paper link and wants to download the paper, interpret it, generate reading notes, break down the paper, or output a detailed report. It creates a paper folder in the working directory, downloads the PDF and TeX Source (if available), and generates a Chinese Markdown report. By default it delivers a first draft and does not review automatically; follow-up review is arranged only if the user explicitly agrees. Not for cases where only a short recommendation is needed.
Use when: you need to design a business model canvas, plan a profit model, set a pricing strategy, or design a revenue model. Do NOT use when: the business model is already defined and validated, or only a simple pricing adjustment rather than a full design is needed
Use when: you need to define the feature scope of the first product version, filter MVP features from an existing requirements list, or determine the boundaries of a minimum viable product. Do NOT use when: the product is already launched and needs a full feature set, or you only need to organize requirements without trimming scope
Use when: multiple requirements need ordering, resources are limited and you must decide what to do first, or conflicting requirements need objective scoring. Do NOT use when: there is only one requirement and no ordering is needed, or priorities have already been set by a manager or the business side
Use when: risk screening is needed after the technical solution is complete, risk identification and assessment before launch, or risk control at key project milestones. Do NOT use when: the project is very small and risks are under control, or a complete risk management mechanism already exists and does not need to be built anew
Use when: market research data collection, competitor information gathering, industry sentiment monitoring, compliance policy checks. Do NOT use when: complete data is already available and no supplementation is needed, or only internal data analysis is required without external information
Discover all possible analysis domains for an artifact. Finds obvious and non-obvious angles — architecture, security, but also marketing positioning, user psychology, regulatory implications, teaching value. Use before prism-scan or prism-full to explore what's worth investigating.
Format messages for Slack with pixel-perfect accuracy. Converts Markdown to rich HTML (for copy-paste into Slack) or Slack mrkdwn (for API/webhook). Use when the user asks to write a Slack message, announcement, or notification, format something "for Slack", preview how content looks in Slack, or send a message via Slack webhook. Also trigger when user mentions Slack formatting, mrkdwn, or wants to share Markdown content in Slack channels.
Use for strategic thinking, or when the user must choose a direction under constraints: "where should we focus?", "how do we win?", "roadmap for next year", "what should we not do?". Ends in explicit bets and risks. Skip for step-by-step implementation.
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.