Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
Discover your DISC personality type and install personalized AI communication skills. Use when someone mentions personality, communication style, DISC, how AI should talk to them, how to communicate with a coworker/boss/teammate, preparing for a meeting or difficult conversation, or wants to customize their AI experience. Also triggers on: 'what's my personality type', 'set up my personality', 'personality quiz', 'how should I talk to', 'communication coaching'. Includes interactive quizzes for both flows. Powered by Crystal's DISC framework.
Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
analyze a professor from google scholar, publication lists, personal websites, lab pages, and field-specific bibliographic databases (e.g., DBLP, PubMed, SSRN, PhilPapers, MathSciNet, arXiv, Scopus) to evaluate research strength, mentoring quality, collaboration network, lab resources, research taxonomy, future directions, applicant fit, outreach emails, and interview strategy. designed for students at all levels — PhD applicants, master's students, and undergraduate researchers (capstone/thesis/independent study) — across all academic disciplines. use when the user wants to assess whether a professor or lab is worth applying to, compare advisors, prepare a cold email, find a thesis or capstone advisor, infer future research openings, or build a structured dossier from public academic evidence.
Push message notifications to WeChat/App via Server Chan (Fangtang). Use this skill when you need to push execution results, alerts, task completion status, and more to your phone (both Server酱 Turbo SCT and Server酱³ SC3 are supported, automatically identified by the SendKey prefix). Supports titles, Markdown body, and optional parameters such as tags/short/channel.
Guide learning and deep understanding through proven methodologies (Socratic, Feynman, Problem-Based). Use when user says "help me understand", "teach me", "explain this", "learn about", "socratic", "feynman", "problem-based", "I don't understand", "confused about", "why does", or wants to truly grasp a concept.
Read your WeCom (企业微信 / WeCom / Work Weixin) contacts, send app & group messages, create and read WeDoc docs/smart sheets, and manage schedules (日程) and meetings (会议) via the WeCom server-side API as a self-built app. Use when the user mentions 企业微信, WeCom, 通讯录成员/部门, 应用消息, 群机器人/应用群聊, 企业微信文档/智能表格, 企业微信日程 or 会议, or a qyapi.weixin.qq.com call.
ADHD Progress Hub continuity protocol for substantial coding work. Use the operator's adhd-hub MCP when starting/resuming meaningful project work, pausing incomplete work, finishing a tracked task, or setting a reminder. Use the forge mailbox when Hub MCP is unavailable to a remote agent. Do not use for trivial questions, read-only lookups, or tiny edits.
Enters idea-maturation mode — researches, analyzes critically, points out trade-offs and suggests improvements without creating or executing anything until the user explicitly asks. Use when the user wants to explore, discuss or refine an idea before implementing it. Triggered by phrases like "quero criar", "tenho uma ideia", "pensa comigo", "me ajuda a planejar", "vamos fazer um brainstorm", "entra em modo brainstorm", or any product, feature, system, skill or workflow idea not yet specified enough for implementation. Has a specialized lens for development project specification — also activate when the user wants to "especificar um projeto", "levantar os requisitos", "montar a spec antes de codar", "definir a arquitetura antes de começar", or describe a system they intend to build. Also activates when the user asks to document, summarize or preserve in markdown a brainstorm already in progress or just concluded, regardless of topic (system, process, email, idea, argument, etc.), and when they want to resume a saved brainstorm ("continua o brainstorm de ontem", "retoma esse brainstorm", or pointing to a brainstorm-*.md file).
Fetch, rank, and enrich recent arXiv and Hugging Face papers. English triggers: “fetch papers”, “fetch papers from the last three days”. This is pipeline stage 1. Paper fetching (step 1 of a 3-step pipeline). Fetch the latest arXiv + HuggingFace papers, score and filter them, enrich their information, and output daily_papers_enriched.json to a shared temporary directory for subsequent skills. Triggers: “论文抓取”, “跑一下论文抓取”. Supports multi-day mode: “过去3天论文推荐”, “过去一周论文推荐”, “过去一周的论文”, “抓 3 天的论文”, “最近5天”
Read, study, and answer questions about long books and papers without loading the whole text into one context window, keeping page-anchored notes as a reusable workspace. Use whenever the user asks to read, study, summarize, analyze, review, or answer questions about a long book, textbook, PDF, EPUB, thesis, dissertation, survey paper, or any document of roughly 50+ pages, in any language (Vietnamese "đọc sách", "tóm tắt sách", "phân tích luận án"). Also use when a `{slug}-notes/` workspace from a previous session sits next to a source file and the user asks a follow-up question about that book. Not for short documents (under ~30 pages) that fit in context; read those directly.
Run a game development post-mortem rooted in the GDC tradition. Triggers on: "retrospective", "retro", "post-mortem", "lessons learned", "what went right", "what went wrong", "kill list review". Do NOT invoke for design document review (use game-design-review) or playtesting (use game-playtest). Part of the AlterLab GameForge collection.
A cognitive framework based on learning first principles, providing learning method diagnosis, efficiency assessment, and optimization advice. Use when: (1) Diagnosing if current learning methods align with first principles, (2) Evaluating learning plan efficiency and time investment, (3) Analyzing learning behavior problems and providing improvement suggestions, (4) Determining if learning content is worth the time investment. Core principle chain: Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice.
Learning resource roundup assistant. A skill that helps users collect, filter, and organize learning resources. Use when the user asks for a roundup of learning materials in a field, such as "help me gather quality machine learning resources" or "recommend front-end development learning resources". Supports aggregating, rating-based filtering, and categorizing many resource types, including books, courses, papers, documentation, and blogs.
Surface the top 3 mental models from contemporary thinking that best illuminate a given problem or situation. Use when user says "what mental models apply here?", "help me think about this", "what framework should I use?", or "reframe this problem". Applied analysis showing how each model reframes or clarifies the issue.
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
Run graph queries on Obsidian vault link structure: neighbors (N hops), shortest path, connected clusters, hub notes, bridge/articulation points, enriched orphans, relationship summaries, vault-wide statistics. Supports configurable frontmatter relationship fields. Use for: knowledge graph, note relationships, graph query, link analysis, note connections, hub notes, cluster analysis, bridge notes, relationship summary, vault stats, find path between notes, analyze connections, show orphans, 筆記關係, 連結分析, 孤立筆記, 知識圖譜, 樞紐筆記, vault 統計.
A dialogue-style Skill that helps you reflect without blame on situations where you are stuck at work, in study, in housework, or in personal projects, using five steps as clues to find unseen assumptions and the next step. Use it when you want to sort out procrastination, perfectionism, fear of starting or submitting, or a stall after trying. Not for simple execution, explanation, minor fixes, or comprehensive planning.
Structured peer review of manuscripts and grants. 7-stage evaluation: initial assessment, section review, statistical rigor, reproducibility, figure integrity, ethics, writing. Covers CONSORT/STROBE/PRISMA and report structure. For evidence quality see scientific-critical-thinking; scoring see scholar-evaluation.
Use when the user needs product management workflows such as RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, go-to-market strategy, feature prioritization, research synthesis, or requirements documentation.
Programmatic PubMed access via NCBI E-utilities REST API. Covers Boolean/MeSH queries, field-tagged search, endpoints (ESearch, EFetch, ESummary, EPost, ELink), history server for batches, citation matching, systematic review strategies. Use for biomedical literature search or automated pipelines.
Deep recursive research with a self-regulating loop up to PhD level. Applicable to any domain (science, technology, business, art, humanities). Uses WDM + Munger inversion for autonomous decisions, trusted-source tiering, and disk checkpointing to survive context limits.
Use Slax Reader CLI to save URLs/bookmarks to the user's reading library, list and get bookmarks, authenticate with reader-cli, check account status, archive URLs, tag bookmarks, and handle reader-cli upgrade or skill sync hints. Trigger when the user asks to save, bookmark, archive, list, get, or organize web links with Slax Reader.
Single-dimension execution and multi-source search integration within deep research; use when plan.json already defines dimensions and you need to call the appropriate search capabilities according to dimension.search_strategy for multiple rounds of retrieval, evidence screening, and cross-validation, then write to sub_reports/{dimension_id}.md.
Research Zhihu and Chinese-community viewpoints with source links: 知乎/知乎链接、真实体验、口碑、避坑、大家怎么看、国内用户观点、中文社区、国内热点、查中文来源. Use for requested Zhihu search, question answers, Zhida answers, hot lists, account quota, authorized user/creator data, knowledge bases, PDF/PPT tasks, or zhihu-search setup. Do not trigger merely because a question is in Chinese. Exclude repository-local code questions, pure math or logic, translation, and user-provided content unless external community evidence is requested; respect no-browsing and source restrictions. Account data, uploads, task creation, and OAuth require an explicit request.
Academic paper writing assistant for top-tier conferences and journals with AIGC-aware natural voice and figure quality enforcement. Triggers when: Writing academic papers or articles, needing literature search and citation formatting, preparing manuscripts for conference submission, creating paper structure, generating SVG/PDF figures, drafting reviewer response letters, or reviewing/polishing to reduce AIGC detection rates. Commands: - /paper new <topic> - Start new paper with topic analysis - /paper search <keywords> - Search and collect literature - /paper cite - Format citations properly - /paper structure - Generate paper outline - /paper review - Review, polish, and reduce AIGC markers - /paper detect <text> - Analyze AIGC features in text - /paper zh <topic> - Write Chinese journal article (CCF/知网 format) - /paper figures - Generate publication-quality SVG/PDF figures - /paper rebuttal - Draft reviewer response letter Capabilities: AIGC-aware academic writing, natural academic voice, literature search from Google Scholar/arXiv/DBLP/Semantic Scholar, citation formatting (IEEE/ACM/APA/GB-T7714), paper structure generation, mathematical notation, Chinese academic publishing, SVG/PDF figure generation, reviewer response drafting, iterative review with AIGC rate reduction, opencode-specific collaborative writing patterns
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.