Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Documents
Use for applicant-facing diagnosis or re-audit of a Chinese NSFC (国自然) application draft — 本子把脉、本子体检、帮我看国自然本子、申请书修改建议、标书逻辑诊断、青年/面上/地区基金申请书修改、对照已中本子、科学问题凝练、代表作支撑、选题撞题核查 or 申请代码检查. Accepts PDF/DOCX/Markdown/text and checks title, abstract, rationale, key scientific questions, research contents, innovation, feasibility, research basis and cross-section consistency, calibrated to the application year and form. Does not write applications from scratch or provide formal expert-review opinions.
Create a Product Requirements Document following proven PM template structure. Use when asked to write a PRD, product spec, feature specification, or requirements document for a new feature or product. Produces a complete PRD with problem statement, user stories, functional requirements, technical considerations, and success metrics.
Write a structured project status report for any project. Use when asked to write a project update, status report, RAG report, project dashboard narrative, or weekly project communication. Produces a clear status report with RAG ratings, milestone progress, risks, and decisions needed.
Convert code projects into an Obsidian knowledge base. Activates when the user mentions obsidian, project documentation, knowledge base, analyzing a project, or converting a project. [After activation, you must]: 1. First read this SKILL.md file in full 2. Understand the AI writing rules (default to 00_Inbox/AI/, append-only, unified Schema) 3. Execute STEP 0: use AskUserQuestion to ask the user for confirmation 4. Start STEP 1 project scanning only after user confirmation 5. Strictly follow the order STEP 0 → 1 → 2 → 3 → 4 [Prohibited actions]: - Do not start analyzing a project without reading SKILL.md - Do not skip STEP 0 user confirmation - Do not create directly in 30_Resources (go to 00_Inbox/AI/ first) - Do not decide the output location on your own
Read-only proofreading pass over lecture `.tex` or `.qmd` files. Checks grammar, typos, overflow, terminology consistency, and academic writing quality; produces a report without editing. Use when user says "proofread", "check for typos", "look for grammar issues", "copy-edit this", "any writing errors?", or before a lecture release.
Create, customize, or polish application-ready resumes from scratch for university students, new graduates, and internship seekers: supports a Grill Me-style question-and-answer interview to collect experience from zero and generate a PDF; reads job JDs and old resumes to build a requirement–evidence mapping and rewrite accordingly; optimizes the content structure of an existing resume or only polishes the layout without changing facts; and generates six different styles of ATS-friendly PDF resumes at once when the user explicitly requests it. Applies to requests such as "interview me to make a resume", "no resume, Q&A from scratch", "customize a resume based on a JD", "optimize/rearrange/polish an existing resume", and "generate multiple resume styles at once"; supports Chinese/English and computer science, software, AI, data, and other campus recruitment positions. Uses the A-C-R-E structure to review experience and adapts content density as sparse / balanced / dense. Fabricating experience or numbers is prohibited; by default it generates one most suitable single-column resume, and only generates in bulk when the user explicitly asks for a comparison. Do not use for academic application CVs, senior executive resumes, portfolio websites, submitting applications on someone's behalf, or pure mock interviews.
Build a standalone multi-page Markdown wiki package for a large software repository after reading and analyzing the whole codebase. Use when the agent is asked to create repository wiki documentation, onboarding docs, architecture guides, codebase tours, maintainer handbooks, or deep explanations of modules, core code paths, algorithms, design decisions, tradeoffs, tests, tooling, and operations for code learners or new maintainers. Optimized for large repositories with hundreds of thousands of lines of code where maintainers need broad coverage and deep subsystem documentation. The generated wiki must live in an independent package, usually `wiki/` or `maintainer-wiki/`, and must not be mixed into existing `docs/`, `website/`, or product documentation apps unless the user explicitly overrides this. Also supports optional Rspress/static documentation site setup when the user explicitly asks to publish or deploy the generated wiki. Supports Markdown output with Mermaid, Graphviz, and KaTeX where useful.
When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps.' Use this for any document or asset that helps a sales team close deals. For competitor comparison pages and battle cards, see competitor-alternatives. For marketing website copy, see copywriting. For cold outreach emails, see cold-email.
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
Implements Syncfusion Blazor PDF Viewer (SfPdfViewer) for viewing and editing PDF documents in Blazor applications. Use this when working with PDF rendering, annotation, text search, form filling, or document navigation in Blazor.
Design hands-on technical nonfiction chapters as runnable labs, worked examples, exercises, checkpoints, troubleshooting paths, and reader outcomes. Use when turning technical book sections, tutorials, self-hosting chapters, DevOps guides, programming lessons, or infrastructure explanations into practical labs that readers can complete and verify.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Compile a Beamer LaTeX slide deck with XeLaTeX (3 passes + bibtex). Use when user says "compile", "build the slides", "rebuild the PDF", "run latex", "render the tex", or asks why a `.tex` file isn't producing a PDF. Operates on `Slides/*.tex`.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
Creates selected frontend Markdown documentation from code evidence, including frontend architecture/design docs, feature-system maps, developer onboarding, route and data-flow docs, DESIGN.md compliance, and gap analysis for React, Vite, TanStack Router, TanStack Query, Tailwind CSS, design systems, UI quality, accessibility, testing, and maintainability issues. Use when the user asks to document a frontend app, map UI architecture or frontend systems, onboard frontend developers, audit frontend documentation gaps, document systems/<domain> feature architecture, validate frontend adherence to DESIGN.md, evaluate gaps against UI quality practices, or produce objective frontend docs. Do NOT use for backend docs, generic README writing, or implementing frontend changes.
This skill should be used when the user asks to convert an academic paper in LaTeX from one format (e.g., Springer, IPOL) to another format (e.g., MDPI, IEEE, Nature). It automates extraction, injection, fixing formatting, and compiling.
Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.
WeChat Official Account article management tool. Used to manage the publishing and updating of WeChat Official Account articles. Use cases: publishing articles to the WeChat Official Account draft box; updating existing draft content; uploading image assets to the WeChat asset library. Core features: convert documents to WeChat Official Account HTML with AI, then use Python scripts to call the WeChat API for asset upload and draft management.
This skill should be used when the user asks to "update study", "analyze new experiments", "update experiment document", or "refresh study notes". Produces academic-paper-quality experiment reports with matplotlib plots, executive summary with comparison tables, implementation structure, experimental results with figure interpretation, proposed improvements with code examples, hypotheses, limitations, and LaTeX PDF export with figures. Features incremental detection (only analyze NEW experiments), data extraction to DataFrame, automated plot generation, iterative writing improvement loop with quality criteria, zero-hallucination verification, and LaTeX PDF export. Usage - `/update-study logs/experiment.log study.md` or `/update-study "logs/exp1.log logs/exp2.log" results/ablation_study.md`
Download WeChat official account articles in multiple formats (HTML, PDF, Word, Markdown, TXT, MHTML), including single article download, collection (appmsgalbum) download, local bulk workflows, and metadata export. Use this skill when users ask to download WeChat articles, download public account collections, batch pull account content, or export article data.
Use when preparing anything that announces a release to the people who consume it — CHANGELOG entries, GitHub release descriptions, version announcements, upgrade or migration guides, or deprecation notices. Triggers include "write the changelog", "release notes for v2.3", "summarize what changed since the last release", "what do users need to know about this upgrade", and cutting a tag.
Free Elicit-columns analog — ingest N PDFs (or any MarkItDown-supported document) and build a per-paper evidence table with user-defined columns, one row per paper and one column per attribute/question you want pulled from every source. Use when extracting structured data across many papers into a comparison table or data-extraction sheet (sample size, methods, main finding, effect, population/intervention/outcome, limitations), screening a corpus into a spreadsheet, or pulling the same fields from a stack of PDFs into CSV/Markdown. Routes conversion through MarkItDown; offline heuristic backend by default, optional LLM backend for precise answers. Part of the AlterLab Academic Skills suite.
Drafts evidence-anchored academic reference and recommendation letters across types — graduate admission, faculty hiring, tenure/promotion external review, fellowship, and award nomination — from a structured prompt of candidate accomplishments, role context, evaluator relationship, and audience, calibrating specificity and register to the letter type and running a no-fabrication guard that flags unsupported superlatives, unanchored rankings, and claims with no evidence in the supplied dossier. Ships scripts/letter_scaffold.py to emit a typed section skeleton and scripts/claim_guard.py to lint a draft for evidence-free assertions. Use when the request is to write a recommendation or reference letter for a student or colleague, a tenure or promotion external-review letter, a fellowship or award nomination, or to check a letter draft for unsupported claims. For a candidate writing their own CV, research statement, or career narrative prefer alterlab-academic-career. Part of the AlterLab Academic Skills suite.
Drafts course-level generative-AI use policies and syllabus statements: assigns each graded task a permitted/restricted/prohibited tier (modeled on Cornell's prohibit/allow-with-attribution/encourage framework), writes the disclosure clause with current APA (2025: cite the shared chat or the tool) and MLA generative-AI citation templates, and adds assessment-integrity, accessibility, and equity language bound to the institution's own academic-integrity code. Ships scripts/policy_builder.py to emit a paste-ready statement and scripts/policy_lint.py to flag a vague or self-contradicting draft. Use when the request mentions a syllabus AI policy, a course statement on ChatGPT or generative AI, an academic-integrity clause for AI tools, an AI-disclosure rule, or per-assignment permitted/prohibited AI tiers. For full course/backward design, syllabus, or rubrics use alterlab-teaching-design; for human-subjects AI-tool ethics use alterlab-research-ethics. Part of the AlterLab Academic Skills suite.
Plan and synthesize pre-draft reader conversations for useful nonfiction books, including listening interviews, teaching calls, reader-language capture, promise validation, scope refinement, and TOC testing. Use when validating a practical book idea, finding target readers, preparing interview prompts, testing a table of contents, or turning reader conversations into book decisions.
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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.