Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Use when the user wants to schedule, automate, trigger, or be reminded of anything — "remind me…", "every morning…", "in two hours…", "when a new Gmail arrives", "when this record changes", "post a weekly summary". Decides between a reminder, an automation, and a skill, and builds the correct payloads.
Check the evidence, biases, alternative explanations, and reporting limits required by research conclusions before execution or submission. Use when the user asks “审我的研究设计”, “当严格审稿人”, “攻击这个结论”, or requests the rw-research-referee workflow. Runs without a private local workspace or preset research lab; use user-provided material and bundled public-source methods
Save creative milestones from self-media work as files, manage versions, verify paths, generate complete publishing packages, and update the content index. Use to save a complete first draft for a platform, a multi-platform collection, short-video scripts, storyboards, final drafts, publishing packages, and retrospective reports, or when the user says “save this,” “organize the deliverables,” “archive,” or “generate a publishing checklist.” Do not save title tweaks, sentence deletions, or temporary alternatives as separate versions.
Search the public web through Tavily and return structured results with URLs and snippets. Use when an agent needs current information, source discovery, link lookup, news or finance search, or a fallback for unavailable built-in web search. Do not use for private or authenticated pages.
Filing gate for ALL brain writes. Consulted before creating any new brain page to determine the correct path. Reads the ACTIVE schema pack via `gbrain schema show --json` — no hardcoded directory table. Also runs periodic taxonomy drift detection via `gbrain schema review-orphans`.
Precise DingTalk contact lookup. Use when a userId is already known to look up details, department, title or email, to reverse-lookup a user by full phone number, or to query yourself, department members and roles. Fuzzy name search, employee ID, responsibilities and reporting lines go to dingtalk-aisearch; once you have the userId, use this skill to fill in details. Command prefix: dws contact.
DingTalk file management (storage layer, covering DingTalk Drive and document spaces). Use when the user mentions ordinary files or folders in 钉盘/文档空间/我的文档, looking up/recently accessed or edited document lists/upload/download/copy/move/rename/delete/recycle bin/permissions/comments/metadata, or comparing local and DingTalk Drive folders, pulling, pushing, two-way syncing; also handles storage management of online document nodes. Document body editing and export go to dingtalk-doc; explicit knowledge base spaces and node organization within them go to dingtalk-wiki. Command prefix: dws drive.
Generate quizzes from study materials with multiple question types (MCQ, True/False, Fill-in-blank, Short answer, Matching). Supports difficulty levels and answer keys. Use when creating practice quizzes, test prep materials, self-assessment tools, or knowledge checks from notes, textbooks, or any learning content. Triggers - create quiz, generate questions, make practice test, knowledge assessment, quiz from notes.
Read academic papers from a bare arXiv abs/pdf/html URL, a PDF, a paper title, or Zotero. Use for "read this paper", "analyze this paper", "读一下 XXX", "读一下这篇", "帮我读", "看一下这篇论文", "论文笔记", quick summaries, critiques, and Zotero collection reading. A standalone arXiv link or ordinary reading request defaults to full reading and automatic note saving in the configured Obsidian/Markdown library. Honor explicit depth, destination, and no-save requests; a citation used for another task does not trigger reading.
Desktop automation CLI for AI agents (macOS, Linux, Windows). Screenshot, click, type, scroll, drag with native Zig backend. Use this skill when automating desktop apps with computer use models (GPT-5.4, Claude). Covers the screenshot-action feedback loop, coord-map workflow, window-scoped screenshots, and system prompts for accurate clicking
Automate the WeChat macOS desktop client. Uses AppleScript + cliclick to send messages, read chat history, search conversations, scroll, and more. Trigger this skill when users mention WeChat, sending someone a message, messaging a group, checking what a group is talking about, WeChat automation, or scheduling WeChat messages. Supports background mode—it automatically switches back to the previous app after operations without interrupting the user's work.
Verify that every reference in a manuscript really exists and matches its metadata, catching hallucinated, corrupted or mismatched citations before submission. Use when checking a .bib file or reference list, after an AI assistant drafted citations, when a DOI may point to the wrong paper, when adding missing DOIs, or before camera-ready. Queries Crossref, OpenAlex and arXiv; zero dependencies.
dontbesilent content structuring system. Turn a large local collection of drafts, posts, topics, case studies, and course materials into a content structuring project that can grow over time: first audit its size and scope, then create a project, copy materials, extract content units, and generate topic maps and topic assembly drafts. Triggers: /dbs-content-system, /内容结构化系统, “把我的内容做成结构化系统”, “把本地素材变成可重组系统”, “帮我搭内容资产工程”, “我想把旧内容变成可复用资产”. Content structuring system. Audits local content volume, then builds a reusable content knowledge project with units, topic maps, and assembly drafts. Triggers: /dbs-content-system, “build a content structuring system”, “turn my archive into reusable assets”.
Read and send Microsoft Teams chat messages via Microsoft Graph v1.0. Use when the user mentions Microsoft Teams chats, a 1:1 or group chat, reading recent Teams messages, or sending a Teams chat message. (Channel messages are not covered — they need admin-consented scopes.)
Reads, searches and exports local Claude Code and Kimi CLI history without resuming work: timelines, verbatim user input, keyword or fuzzy recall, file recovery from transcripts, and which session ran a given command in a known time window. Use when the user asks what was said, wants a session ID or original context, needs proof of what a session contained, or needs past-session runtime evidence about commands, tool calls and hook runs — query this index instead of raw-scanning transcript files. Not for Codex (use read-codex-history); with no platform or several named, start at local-conversation-history.
Focused product-management skills spanning the full lifecycle: discovery (user interviews, problem validation, JTBD, research synthesis), strategy (competitor analysis, positioning, strategy docs), prioritization (RICE, Shape Up scope-cutting and bet-sizing), evidence-first PRDs, plus launch plans, North Star metrics frameworks, A/B experiment design, and Now/Next/Later roadmaps.
dontbesilent interactive learning. Breaks a topic into a series of learning articles, adjusting the depth, angle, and pace of each subsequent article based on the user's feedback on the previous one. Triggers: /dbs-learning, /dbs-learn, /交互式学习, “Teach me a topic”, “Continue with the next lesson”, “Write the next lesson based on my feedback”
AI search: semantic people search, cross-source topic retrieval, and behaviour tracing. Use when finding people semantically, or when the target is unknown and you need to discover content by topic or behaviour. Native recent lists go through the owning product; exact lookup by full mobile number goes through dingtalk-contact. Prefix: dws aisearch.
A Douyin keyword search and structured evidence-gathering adapter that uses only the installed and logged-in OpenCLI; answers search requests independently or gathers this episode’s Douyin evidence for 真人口播①, but does not decide the final topic. Use when the user says “抖音搜索,” “搜一下抖音,” “抖音上搜,” “抖音关于,” “抖音上有什么,” or “douyin搜索,” or when the bianpai/topic-selection workflow requires validating Douyin keywords.
Create and manage PostHog reminders — private, human-paced nudges that fire as in-app notifications on a schedule, optionally linked to a PostHog resource. Use when the user says "remind me to…", wants a one-off or recurring nudge (daily/weekly/monthly/yearly, a cron schedule, or a specific date/time), wants to be reminded to look at a dashboard, insight, experiment, feature flag, survey, notebook, replay, or error, or wants to list, change, or cancel their reminders. Covers when to pick a reminder over an alert or subscription, the one-off vs recurring vs cron schedule field mappings, timezones, and attaching a resource.
Reads, searches and exports local OpenAI Codex history without continuing work: session inventory, timelines, verbatim user input, indexed search, and rollout identity/fork lineage. Use when the user asks what they told Codex, wants a Session ID, or evidence of what a run did. Not for Claude Code (use read-claude-code-history); with no platform named, start at local-conversation-history.
Build a knowledge base (KB) that AI can genuinely query: organize what you know about a domain into concepts (for understanding) and recipes (for doing), with an entry point, quick lookup, and size limits that keep the material usable. Create the project index on first use and register each new domain. For legislation and standards (normative profile), record each rule’s validity, its source with SHA-256, conflicts between sources, and the rule → source → test map. Recommended before starting an SDD workflow. Content is always reviewed by a professional: AI organizes and drafts, while the person with technical responsibility is accountable for what gets recorded. Use when the user wants to teach their context to AI, catalog laws, standards, manuals or internal policies, document a process, or complains about having to explain the same things again in every conversation.
dontbesilent personal decision system. Turn any domain that requires long-term tracking (business, relationships, health, career, learning, investing…) into a local knowledge project: a four-layer structure, source tags, immutable snapshots, and a concept library that can distill patterns. Triggers: /dbs-decision, /决策系统, /决策立案, /结果回填, /状态画像
dontbesilent goal clarification. Uses Wittgenstein’s philosophy of language to audit fuzzy goals into checkable deliverables. Triggers: /dbs-goal, /目标, “help me clarify my goal”, “I want to build a personal brand”, “my goal is to become…”, “I want to become more…”
dontbesilent good-question generator. Turns fuzzy problems into briefs that an Agent can reason about, critique, and verify, and assesses how much of the problem can be solved automatically. Triggers: /dbs-good-question, /好问题, /问题说明书, /Agent可解性, “can this problem be solved automatically”, “help me clarify the problem”
(NS) Gated PM: clarify, RICE/WSJF, sprint, PERT/Monte Carlo; PRD (product discovery doc); product/project roadmap (multi-version); version handoff; release delivery report for leadership (relatório de entrega da versão, deploy report para diretoria, o que vai para produção); risk/status/OKR; orçamento, Function Points, proposta comercial, preço do ponto de função, quanto custa o PF; cronograma P100/P85/P50. Use on transcripts, backlog, timeline, delivery date, status, roadmap, roadmap do projeto, roadmap de produto, PRD, product requirements document, documento de requisitos de produto, versões entregues/planejadas, orçamento, cotação, cronograma, handoff, fecha a versão, valor do PF, não sei o preço do ponto de função, dúvidas do dev, perguntas da equipe sobre o PRD — even if PM unnamed. Do NOT use for coding, SDD requirements.md, GitLab issue execution, or `/ns-requirements-enricher`.
Every Cal.com feature, plus offline agendas, composed booking flows, and analytics no other Cal.com tool ships. Trigger phrases: `book a meeting on cal.com`, `what's on my calendar today`, `find an open slot`, `reschedule my next booking`, `audit my cal.com webhooks`, `use cal-com`, `run cal-com-pp-cli`.
Search 51M+ podcast episodes and 4.4M+ podcasts via Podscan—full transcripts, AI-extracted entities, mentions, and brand-safety analysis. Trigger phrases: `search podcast transcripts`, `find podcasts mentioning`, `who's talked about <topic> on podcasts`, `use podscan`
Ask structured questions one at a time to gather requirements, context, or clarification. Each question includes its intention and current assumptions. Use when the user wants to be interviewed about a topic, gather requirements, or needs help thinking through a problem step by step.
DingTalk calendar and meeting rooms. Use when the user says 约会议/查日程/订会议室/查闲忙/加参会人/改期/取消会议/今天的日程/本周日程/共同空闲. Does not cover starting video meetings/inviting attendees/in-meeting controls (use dingtalk-misc), AI meeting notes (use dingtalk-minutes), or to-do tasks (use dingtalk-todo). Command prefix: dws calendar.
DingTalk to-do / TODO. Use when the user says 创建待办/TODO/任务提醒/指派任务/标记完成/查待办/紧急待办/循环待办/批量建待办/逾期待办. Does not cover daily/weekly reports (use dingtalk-misc), approvals (use dingtalk-misc), or calendars (use dingtalk-calendar). Command prefix: dws todo.
Manage Linear issues, projects, and workflows via CLI. This skill should be used when the user wants to create, list, update, or search Linear issues, manage projects or milestones, or interact with their Linear workspace. Triggers on "create a task", "add a Linear issue", "list my issues", "update GLE-123", "what's in my backlog", or any Linear-related request.
How to work in a Plain Notes project (the `plain-notes` starter pack): a flat notes/ folder plus a daily/ journal. The “I just want to write” layout. Read when the project has these folders, or when asked to jot a note, capture a quick thought, or write today's journal entry. Carries the linking habit and daily-entry behavior so templates and folder descriptions stay minimal. Complements the platform `open-knowledge` skill; does not replace it.
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.