Document Claude Skills
2 253 document skills from 443 authors. They read and assemble documents, spreadsheets and slide decks. Half of them fit into 1 829 tokens or less — that is what one costs your context window when the agent loads it. 571 ship runnable scripts rather than instructions alone. 24 of them cannot work without an MCP server, most often rube. We also found 384 copies of these same skills sitting in other people's repositories — counted once here, not 384 times.
2 253 unique 443 authors 1 294 updated this month 183 from vendors
用于审阅故事设定、手法、程序链、证据载体或规则文档。适合检查规则是否可执行、边界与代价是否明确、是否可证据化、是否具备程序摩擦与镜头化表达，并输出可落库、可回写的设定审阅报告。关键词：审故事设定、设定审阅、规则边界、证据化、程序摩擦、设定报告。
用于将“小红书/”目录内指定章节批量上传到小红书创作者后台并暂存草稿。支持按 README.md 读取作者笔名、小说名称与合集映射信息，自动执行登录状态检查（需用户手动登录）、按新增/修改分流填写标题与正文并“暂存离开”，同时回写无章节Id场景下的草稿追踪记录。关键词：小红书上传、长文笔记、暂存离开、草稿箱、长文合集、批量传章。
用于审阅都市悬疑故事设定、手法、程序链与证据载体文档。作为题材包装层与兼容入口，负责补充异常证据、程序摩擦与现实代价等题材裁判口径，并明确要求优先强制加载并使用 `通用-审阅故事设定`。关键词：都市悬疑设定审阅、程序链、证据载体、规则代价。
用于审阅都市职场故事设定、手法、程序链与证据载体文档。作为题材包装层与兼容入口，负责补充异常证据、程序摩擦与现实代价等题材裁判口径，并明确要求优先强制加载并使用 `通用-审阅故事设定`。关键词：都市职场设定审阅、程序链、证据载体、规则代价。
Based on FeiShu(飞书) / Lark's OpenAPI MCP server, manage user information, chats, emails, cloud documents, multidimensional tables, tasks, calendars, etc.
| Compare and merge two design docs for the same feature into a single source of truth. Use when you have competing or complementary design/implementation docs (e.g. from separate design runs) that need reconciling into one unified document.
| After implementing a new feature or fixing a bug, make sure to document the changes. Use when writing documentation, after finishing the implementation phase for a feature or a bug-fix.
| Review design, implementation, and task documents produced by design. Evaluates document quality, internal consistency, and technical soundness. Use after design completes and before starting implement.
| After implementing a new feature or fixing a bug, make sure to document the changes. Use when writing documentation, after finishing the implementation phase for a feature or a bug-fix.
| Compare and merge two design docs for the same feature into a single source of truth. Use when you have competing or complementary design/implementation docs (e.g. from separate design runs) that need reconciling into one unified document.
| Review design, implementation, and task documents produced by design. Evaluates document quality, internal consistency, and technical soundness. Use after design completes and before starting implement.
Convert markdown documents and chat summaries into formatted EPUB ebook files that can be read on any device or uploaded to Kindle.
| 当系统提示需要设计引用格式、信息溯源机制、来源标注系统时调用。适用于文档问答、搜索增强生成（RAG）、代码引用、浏览器辅助等需要让用户追溯信息来源的场景。不适用于纯创作类输出（如故事、诗歌），不适用于无需溯源的常识问答，也不适用于注入防御（虽然两者都涉及内容可信度）。
> End-of-session cleanup routine that captures all session work before context is lost. Use this skill when the user says "wrap up", "wrap-up", "let's wrap it up", "let's wrap up", "wind down", "end session", "that's it for today", "save and close", "let's call it", "close out", "done for today", or any indication they are finishing a work session and want everything documented before starting fresh.
Extract text, tables, and images from PDFs. Use when: extracting data from reports; converting PDF tables to CSV; pulling images from presentations; processing research papers; batch converting PDFs to text
Generate PDF/HTML reports from templates and data. Use when: creating client reports; generating weekly summaries; producing marketing performance reports; automating recurring reports
Use this skill when you need to parse Word/HTML/JSON/Markdown/Excel requirements and produce a structured analysis; triggers include requirements analysis plus and requirement document parsing.
Create polished, audience-tailored presentations from outlines or documents, with support for Marp, reveal.js, Google Slides, and PPTX output formats.
Retrieves and synthesizes relevant information from a knowledge base using RAG techniques to provide grounded context for a given query.
Write clear, searchable help center articles and FAQ entries based on support data, product documentation, and common customer questions.
Draft Terms of Service documents for web applications, SaaS platforms, and digital marketplaces.
Summarize text using extractive, abstractive, hierarchical, and multi-document techniques, producing concise outputs at configurable detail levels.
Detects and analyzes ambiguous language in software requirements and user stories. Use when reviewing requirements documents, user stories, specifications, or any software requirement text to identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications. Provides detailed analysis with clarifying questions and suggested improvements.
Reorganizes markdown documents into well-structured, consistent format while preserving content and improving readability. Use when Claude needs to: (1) Fix heading hierarchy issues (skipped levels, multiple h1s), (2) Generate or update table of contents, (3) Standardize formatting (lists, code blocks, emphasis, links), (4) Improve grammar and spelling, (5) Add missing standard sections (installation, usage, etc.), (6) Remove redundant or duplicate content, (7) Restructure technical docs, READMEs, or long-form content for better organization and flow.
Transforms natural language requirements (user stories, verbal descriptions, business rules) into formal specifications and constraints. Use when converting informal requirements into structured, testable specifications with explicit constraints. Outputs in multiple formats including BDD-style Given-When-Then, JSON Schema, and structured plain text requirements documents.
Summarize long Isabelle or Coq proof scripts into high-level logical steps and reasoning flow. Use when users need to: (1) Understand the structure of a complex proof, (2) Document proof strategies for others, (3) Extract the key reasoning steps from verbose proof scripts, (4) Create readable proof outlines from detailed tactical proofs. Produces hierarchical outlines with moderate detail showing proof structure, main cases, key lemmas, and reasoning flow for both Isabelle/Isar and Coq proofs.
Extract and summarize core features, constraints, and priorities from requirement documents. Use when analyzing PRDs, RFCs, business requirements, user stories, epics, or any requirement documentation to identify must-have features, technical constraints, priority levels (P0/P1/P2/MoSCoW), and key decision points. Triggers when users ask to summarize, analyze, extract, or understand requirements from documents.
Generate concise, structured summaries of requirements for quick team understanding. Use when analyzing requirements from text documents (MD, TXT, DOCX) or technical specifications to create bullet-point summaries that highlight core functionality and dependencies/constraints. Ideal for sprint planning, stakeholder updates, team onboarding, or any situation requiring rapid comprehension of requirement documents.
Automatically derives TLA+ properties (invariants, safety, liveness) from natural-language requirements or structured requirement documents. Resolves ambiguities, asks clarifying questions for underspecified requirements, and outputs TLA+-compatible property definitions with semantic explanations. Use when translating system requirements, specifications, or behavioral constraints into formal TLA+ temporal logic properties for verification with TLC model checker.
Generate implementation code and tests from written specifications. Use when the user provides specifications (natural language descriptions, formal specs, requirements documents, API specs) and asks Claude to implement the described functionality. Supports data structures, algorithms, classes, functions, and includes automatic test generation to validate implementation against specification.
Translate natural-language requirements or structured specification documents into formal temporal logic properties (LTL, CTL, safety/liveness properties). Use when users need to formalize requirements for model checking, formal verification, or property specification. Handles embedded/real-time systems, hardware verification, concurrent systems, and reactive systems. Resolves ambiguities, asks clarifying questions when needed, and outputs machine-checkable formulas with explanations. Supports multiple output formats (SPIN, NuSMV, Uppaal, TLA+, Maude).
> Builds traceability matrices connecting requirements to design documents to source code implementation, tracking the complete development lifecycle. Use when you need to verify implementation completeness, ensure all requirements are implemented in code, generate compliance documentation, audit requirement coverage, identify orphaned code, or create traceability reports for stakeholders. Supports parsing requirements from Markdown, Word, and PDFs; extracting design from architecture docs and API specs; and scanning source code for implementations. Outputs to Markdown tables, Excel/CSV, and HTML visualizations.
Analyze formal verification artifacts (Isabelle, Coq, Dafny, etc.) and produce structured reports identifying the precise boundary between verified, assumed, and unverified components. Use when assessing verification coverage, understanding trust boundaries, auditing formal proofs, or documenting verification scope. Reports explicitly list verified code, assumptions, axioms, trusted computing base, and unverified components. Conservative and explicit about verification status without attempting to repair or mask gaps.
Extract language-agnostic pseudocode from formally verified programs (Isabelle/HOL, Coq) while preserving verified control flow, data dependencies, and algorithmic logic. Use when: (1) Users have verified code and need readable pseudocode, (2) Documenting verified algorithms for broader audiences, (3) Translating verified implementations to other languages, (4) Creating algorithm specifications from verified code, (5) Preserving verification guarantees in pseudocode form, or (6) Abstracting proof-heavy code to essential logic. Maintains semantic faithfulness to verified implementation.
Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
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
>- Ranked content search over any text corpus using BM25 (via xhluca/bm25s). files/archives, and any local directory. Stateless — builds an in-memory index each invocation, no cache, no persistence. Use when you need ranked multi-word content search beyond grep, or when picking the "most relevant files for these terms" across a corpus. Triggers on "rank these documents", "search this corpus", "find content about X", "which files are most about Y", or multi-word concept queries against a known body of text.
Convert a file from one format to another inside the container — documents, images, audio, video. Routes to the right engine (pandoc, LibreOffice, ImageMagick, ffmpeg) by format pair. Triggers on "convert X to Y", "turn this docx into a pdf", "make a gif from this mp4", "md to docx", "batch-convert these images", or any single-file or batch format change where the source and target extensions differ. NOT for editing content (use docx/pptx/xlsx/pdf skills), creating files from scratch, or reading a file you already have in context.
Generate navigable semantic maps from PDF documents. Extracts section structure via font analysis, then runs LLM extraction per section for claims, symbols, and dependencies — all page-anchored. Produces _MAP.md (progressive disclosure), .symbols.json (definition index), .anchors.json (claim references), and a _USAGE.md snippet for CLAUDE.md. Use when analyzing papers, specs, or legal docs; when asked to "map this document", "index this PDF", "what does this paper say"; or when a coding agent needs grounded reference material from a PDF source. Analogous to tree-sitting but for prose documents.
Generate behavioral/feature documentation for web apps using code-first analysis. Reads source code via tree-sitting to produce _FEATURES.md, with optional visual verification via browser automation. Companion to tree-sitting. Use when documenting app behavior, creating feature inventories, generating behavioral ground truth for agents, or before modifying UI code. Triggers on "map features", "document app behavior", "feature inventory", "what does this app do".
Maintains a structured running-notes document during long work sessions. Use when the user says "session notes", "update notes", "start session notes", "show session notes", or when you recognize the current session has accumulated enough state (decisions, corrections, files touched, errors) that it risks being lost under context pressure. Stores notes as a procedure memory tagged [session-memory, active] so they survive container death within the same session thread.
Reads the visual content of slides, pages, and images the way a human would, not just their embedded text. Use when a PPTX or PDF has image slides, screenshots, charts, scanned figures, or flattened-to-image layouts that the built-in pptx/pdf skills read as empty; when asked to transcribe, describe, OCR, or extract what is shown in an image, slide deck, or document page; or when embedded-text extraction returned little or nothing from a visually rich file. Triggers on 'read this deck', 'what's on these slides', 'transcribe', 'OCR', 'extract text from image', 'describe this chart/diagram', .pptx/.pdf/.png/.jpg with visual content.
| 日記スキル。日次の振り返りとNotion連携。 「日記書いて」「日記の時間」「今日やったこと記録して」「diary」で発動。 「日記」というワードが含まれたら必ずこのスキルを使うこと。memory/への追記だけで終わらせない。
猫の写真を自動判定して猫日記を作成するスキル。写真を送ると猫かどうか判定し、猫ならNotion猫日記DBに自動保存。毎週ベストショットを選出。「猫日記」「ねこ日記」「猫写真」「今週のベストショット」で使用。
Marp（Markdown Presentation）でプレゼンスライドを作成するスキル。PDF/PPTX/HTMLに変換可能。「スライド作って」「プレゼン資料を作って」で使用。
Notion APIでページ検索・閲覧・作成、ファイルアップロード、画像付き日記作成、個別ブロックの更新・削除を行うスキル。「Notionで検索して」「Notionに日記書いて」「Notionにファイルアップロードして」「Notionの個別ブロックを修正して」で使用。
Query the APIView Copilot knowledge base for guidelines, examples, and memories. Use for: search KB, search knowledge base, find guideline, lookup guideline, search guidelines, search examples, search memories, KB query, knowledge base search, find rule, what does the KB say about.