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 422 copies of these same skills sitting in other people's repositories — counted once here, not 422 times.
2 253 unique 443 authors 2 updated this month 183 from vendors
| 接收任意文本、链接、文档或问题，把“解释一下”升级成真正的学习闭环：先判断值不值得学、该学多深，再用最小验证逼出真实理解，并在必要时动态生成 checkpoint HTML。只要用户明显想“学懂”“吃透”“带我学”“帮我验证我是不是真懂了”，而不是只要摘要、改写或普通解释，就应主动使用本技能。也适用于用户想导出学习卡片、checkpoint 页面、复盘页、学习状态页的场景。
Generate structured software specifications for features, bug fixes, and products. Use when the user wants to create a spec, PRD, feature brief, requirements document, or when starting any new implementation that needs a specification first. Invoke via /spec-writer or when the user says "write a spec", "spec this out", "create a spec", "I need a spec for...", or describes a feature they want to build. Produces adaptive-complexity specs with Job Stories, Gherkin acceptance criteria, and three-tier boundaries. Output is a markdown file ready for agent execution or human review.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Generates formal, structured, and executable implementation plan documents based on specifications.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Generates formal, structured, and executable implementation plan documents based on specifications.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Generates formal, structured, and executable implementation plan documents based on specifications.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Generates formal, structured, and executable implementation plan documents based on specifications.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Generates formal, structured, and executable implementation plan documents based on specifications.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Generates formal, structured, and executable implementation plan documents based on specifications.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Generates or updates highly detailed, machine-readable technical specification documents in the /spec/ directory.
Generates formal, structured, and executable implementation plan documents based on specifications.
Scans, analyzes, and documents the existing repository architecture, directories, and file purposes into docs/ARCHITECTURE.md.
Performs consistency and traceability audits across documents (PRD vs Spec vs Plan) to detect missing coverage and scope creep.
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
Workflow to generate a comprehensive Product Requirements Document (PRD) detailing user stories, acceptance criteria, technical considerations, and metrics.
Generates formal, structured, and executable implementation plan documents based on specifications.