「doc」の検索結果

Review all unreviewed documents in Hubdoc. Use when reviewing, processing or publishing Hubdoc receipts and bills.

日本語の概要は準備中です。原文の説明を表示しています。

中国大陆地区法院类案快速检索与《案件检索报告》（DOCX）生成技能。以案件五项要点（案由/法律关系、争议焦点、关键事实、我方诉请与诉讼地位、请求权基础法条）为检索锚点，经一次四问确认即开工（其中**检索地域范围**与**裁判时间范围**为强制选择题，默认范围为「2021年1月1日以后裁判的浙江省范围内的法院案例」，用户点选默认后须回显该范围提示）；按**请求权基础、法律关系、案件事实三要素**判定高匹配——用户**指定**检索特定结果的案例时结果相似度计入评分（四要素满分 10 分），用户**未指定**时结果相似度不作为高匹配考虑因素（三要素满分 8 分）；r1 判定须**核对法条版本与时间效力**，援引已失效旧法条者不得给满分；以语义向量检索为主召回、精确结构检索为条件兜底，本地脚本加权打分后按「得分率 ＞ 法院层级 ＞ 审判程序 ＞ 裁判日期」排序，并检测**同院同日同标题的重复入库**案件、疑似重复者不占入报名额；截取匹配度最高的 5–10 例类案，逐案调详情核验案号并摘录判词原文，最后直接输出含页脚页码的 DOCX 报告（默认保存至桌面）。全流程人工确认 1 次、检索类调用控制在 2 次召回 ＋ ≤10 次详情以内，报告阶段检索冻结。未指定结果时三要素高匹配而结果相反者亦会入报（逐例标注结果方向），指定结果时结果相反者一律剔除；报告内以两处固定声明披露「未设不利先例定向检索路径」的局限。当用户要求「快速检索类似案例」「找几个正向案例」「快速版案例检索报告」「检索 5 到 10 个类案并出报告」「出一份类案检索报告 docx」时使用。需要四象限归位、反向案例定向检索、补充召回多轮迭代或 14 分制硬软条件精判时，应使用完整版技能「案例检索报告Plus」而非本技能。基于华宇元典法律数据 MCP。

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Deep analysis of competitor patent claims: element decomposition, scope interpretation, equivalents prediction, prosecution history estoppel analysis. Automatically converts PDF/DOCX/DOC patent files to structured Markdown via patent-pdf-to-md skill before analysis. Invoke when user asks to analyze/parse competitor patent claims, decompose claim elements, assess claim scope, or perform 权利要求解析/要素分解/保护范围解读. 竞品专利权利要求深度解析：要素分解、保护范围解读、等同范围预判、审查历史限制分析。自动调用patent-pdf-to-md技能将PDF/DOCX/DOC专利文件转换为结构化Markdown后再进行分析。当用户要求解析竞品专利权利要求、要素分解、保护范围时触发。

日本語の概要は準備中です。原文の説明を表示しています。

Creates comprehensive documentation for design systems - token tables, usage guidelines, component examples, and accessibility notes. Use after generating tokens to create developer-friendly docs.

日本語の概要は準備中です。原文の説明を表示しています。

CI/CD caching optimizer for dependency caching, Docker layer caching, and build speed improvements. Activate on: CI cache, build speed, dependency caching, Docker layer cache, turbo remote cache, GitHub Actions cache, pnpm store cache. NOT for: CI/CD pipeline creation (use github-actions-pipeline-builder), deployment strategy (use blue-green-deployment-orchestrator), Docker image building (use docker-multi-stage-optimizer).

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Establish, author, restructure, or audit human-first processor Architecture, Design, Research, Review, and Verification documentation. Use for progressive documentation scaffolding, authority maps, reading paths, document-type content contracts, length-budgeted splitting, or maintainability reviews. Do not use as a substitute for cycle-accurate microarchitecture analysis or RTL implementation.

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Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

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Write technical documentation that matches the measured profile of professionally-written docs. Carries the craft rules derived from 114k words of pre-2022 documentation (SQLite, PostgreSQL, Python, Django, Rust, Go, Pro Git, nginx), the per-Diátaxis-type numeric targets, and the copywriting register for page leads. Use when drafting or rewriting any documentation prose, or when a page is factually right but reads as machine-written.

日本語の概要は準備中です。原文の説明を表示しています。

Workflow Phase 3 — Research and Solution Exploration. Surfaces 2–4 candidate solution approaches with concrete tradeoffs, grounded in current library docs (fetched through the provider named in `.claude/docs-provider.json`) — never in training-data recall. Output lives at `docs/research/<slug>.md`. Candidate ranking and the memo execute in main context; doc/source gathering MAY be delegated to read-only advisory subagents (seed.md §4.2-A).

日本語の概要は準備中です。原文の説明を表示しています。

Multi-container Docker applications with docker-compose — define services, networks, volumes, and orchestrate local development environments

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.

日本語の概要は準備中です。原文の説明を表示しています。

Resolve repository documentation authority, repair reading paths and explanations, or shape a bounded public projection. Maintain docs after a bounded change when indirect reader promises, generated or paired sources, version/evidence boundaries, or unclear authority need attention. Ordinary known updates stay in normal development; not for isolated prose polishing, code review, or broad runtime audits.

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.

日本語の概要は準備中です。原文の説明を表示しています。

Document brownfield projects for AI context. Use when the user says "document this project" or "generate project docs"

日本語の概要は準備中です。原文の説明を表示しています。

Interact with Paddock — AI agent orchestration dashboard. Use when registering agents, managing tasks, syncing skills, or querying agent/task status via Paddock APIs.

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Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.

日本語の概要は準備中です。原文の説明を表示しています。

Finalize documentation changes for production readiness by discovering existing conventions, verifying code-doc alignment, reviewing format/terminology/tone consistency, verifying branch/worktree intent, and structuring clean commits with a post-publish branch/worktree cleanup decision. Counterpart of finalize-and-commit for documentation projects.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Docker — Dockerfile edits, docker-compose services, containers, or the dual-container (fast + Xdebug) setup — even when the user just says 'my container won't start'.

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Especialista em containerização Docker com conhecimento profundo de multi-stage builds, otimização de imagens, segurança em containers, orquestração com Docker Compose e padrões de deploy em produção. Use PROATIVAMENTE para otimização de Dockerfile, problemas em containers, problemas de tamanho de imagem, hardening de segurança, networking e desafios de orquestração.

日本語の概要は準備中です。原文の説明を表示しています。

Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.

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Use when the 文档/交付 role maintains client-facing project delivery document packages, especially Word/DOCX deliverables such as delivery lists, demo scripts, acceptance forms, change confirmations, quote notes, contract-adjacent materials, README/docs indexes, and internal handoff notes.

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Use when code changes may require documentation updates; maps git diff to candidate docs without auto-editing documentation.

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Use Exasol document-file virtual schemas for federated read-only access to object and file storage — S3, Google Cloud Storage, Azure Blob Storage, and Azure Data Lake Storage Gen2 document files. Covers document-file adapter family selection, the EDML `MAPPING` definition, `CREATE VIRTUAL SCHEMA` usage, refresh workflows, and query-side troubleshooting.

日本語の概要は準備中です。原文の説明を表示しています。

Build document analysis applications with Azure Document Intelligence (Form Recognizer) SDK for Java. Use when extracting text, tables, key-value pairs from documents, receipts, invoices, or building custom document models.

日本語の概要は準備中です。原文の説明を表示しています。