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Extract text from a PDF or a scanned document, with or without OCR.

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把一个目标/主题/文章/截图/数据转成有观点、有节奏、有视觉约束的单文件 HTML 演示（网页 PPT、科技战报、产品拆解、行业观察、路演/发布会 deck、社媒可传播长图）。**7 套各锚定公认设计体系的视觉人格**——技术崇高派 Technical Sublime（工程冷光·技术战报/算力）/ 构成主义 Constructivism（宣言/号召）/ 信息·数据设计（Tufte·数据/图表）/ 判断震慑极简 Luxury（高端品牌/判断）/ De Stijl 新造型（标准/秩序）/ 编辑主义 Editorial（衬线·深度观察）/ 演示禅 Zen（暗墨·思想/品牌 keynote）——用户可指定，否则按内容自动判选并透明告知。token + validator 机检（P0/P1/P2）+ 32 维审计**机器强制设计一致性**；反伪造（不造数据/logo/截图/来源·示意标注）；字体本地子集；图按角色路由（默认 CSS/SVG·要图先探测生图环境）。Generates single-file HTML decks with 7 design-system-anchored visual personas, a semantic layout grammar, locked design tokens, evidence-grading, machine validation (P0/P1/P2 + 32-dimension audit), an anti-fabrication discipline, and image-generation environment detection. Use when the user wants a presentation / deck / slides / 网页 PPT / 战报 / 产品拆解 / 行业观察 / 路演 / 发布会 / 社媒长图, or asks to turn an article / screenshot / dataset into slides. Do NOT use for large data-table training material, strict legal/medical/financial compliance documents, multi-author collaborative PPT editing, plain-text summaries, requests to replicate a brand's official keynote visuals, or any request to fabricate realistic-looking data / fake logos / fake screenshots / fake sources.

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 optimizing Convex database read bandwidth, documents-read cost, query indexes, full-table scans, function-level usage dashboard findings, or code that uses .filter(), unbounded .collect(), N+1 reads, or expensive reactive Convex queries.

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Use when ingesting source material for a writing project, building a knowledge map from notes and documents, identifying research gaps, or preparing a research corpus for content creation.

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。

Work with the @upstash/blob TypeScript/JavaScript SDK for S3-compatible object storage with direct browser uploads, presigned URLs, multipart, and signed reads. Use when storing files or blobs, uploading avatars, images, videos, attachments or user documents, letting a browser upload straight to storage without proxying bytes through a server, generating public or time-limited signed URLs, serving private files, streaming large files with pause and resume, setting cache headers on stored objects, or reaching an S3-compatible bucket from the AWS SDK.

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。

Work with the @upstash/redis TypeScript/JavaScript SDK, a serverless HTTP-based Redis client for Next.js, Vercel, Cloudflare Workers, edge runtimes, and Node.js. Use when adding a cache (cache-aside, write-through, TTL and expiration strategies), session storage and user sessions, a key-value store, leaderboards and rankings with sorted sets, counters, distributed locks, queues with lists, streams and consumer groups, sparse index-addressed arrays and ring buffers (ARSET, ARINSERT, ARRING, ARGREP, AROP), embeddings and nearest-neighbour vector search stored inside Redis (VECTOR commands via redis.vector, separate from @upstash/vector), JSON documents, pipelines and MULTI/EXEC transactions, Lua scripting, read replicas, or full-text search, typo-tolerant search, facets, aggregations, and search over Redis stream entries with Upstash Redis Search (different from regular FT.SEARCH; also available for TCP clients via @upstash/search-redis and @upstash/search-ioredis). Also use when migrating from ioredis or node-redis, when a Redis connection is needed from a serverless function without connection pooling, when integrating @upstash/ratelimit, or when the user says Redis cache, KV store, session store, serverless Redis, or Upstash Redis. Also use when building AI agents on Redis with Upstash AgentKit (agent memory, chat history, RAG tools, tool caching, chat persistence, resumable streams, distributed locks) for the Vercel AI SDK, TanStack AI, or Vercel Eve. Supports automatic serialization/deserialization of JavaScript types.

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。

Design accessible documents. TRIGGERS - Use when user needs help with accessible-document-design related tasks.

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。

Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.

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。

You MUST use this before any creative work — creating features, building components, drafting documents, designing workflows, or modifying behavior. Explores your human partner's intent, requirements, and design before any implementation begins.

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 this skill when writing Phase 1b verification architecture documents. Provides purity boundary mapping, proof obligation design, and tier assignment guidance.

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Audit or tidy a Hyalo knowledgebase for broken links, orphan documents, stale content, and inconsistent metadata.

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Detect and remove the tells of AI-generated writing in BOTH English and Spanish, and read back the evidence honestly. Use when the user asks to "de-AI" / "humanize" / "un-slop" a draft, to examine whether text carries the tells (delve, tapestry, "it's not just X, it's Y", "here's the thing", em-dash overuse, an assistant's own closing line left in the document), to compare documents for overlap, or mentions signs-of-ai / SignsOfAI. Backed by the SignsOfAI engine — for a measured 0–100 score, sentence-rhythm burstiness, originality, citations, a writer baseline or perplexity, hand off to that engine (web app, CLI or MCP server) as described below. It cannot determine who wrote a text and must never imply that it can.

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 the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.

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。

Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.

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。

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

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This skill should be used when the user asks to "generate tasks", "create implementation plan", "break down feature", "write agent prompts", "decompose into tasks", "create work items", or when creating agent-ready task descriptions from PRD and SDD documents.

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Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.

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。

Generate production-ready business documents including freelance contracts, project proposals, SOWs, NDAs, and MSAs with jurisdiction-aware clauses. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) legal frameworks. Includes contract templates, clause libraries, and DOCX conversion. Use when starting client engagements, writing proposals, drafting partnership agreements, or needing GDPR-compliant data processing addenda.

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。

Optimize oversized agent instruction files using progressive disclosure. Handles CLAUDE.md (Claude Code), AGENTS.md (OpenAI Codex / GitHub Copilot agents), and copilot-instructions.md (GitHub Copilot). Auto-detects all three formats in your repo, analyzes content tiers, creates sub-documents using each format's native mechanism, and rewrites the main file with zero information loss. Triggers: optimize CLAUDE.md, AGENTS.md too long, reduce copilot-instructions.md, agent instructions file too large, shrink context file, apply progressive disclosure, instructions file bloated

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。

Converts LaTeX article-class .tex documents to Quarto .qmd format for multi-format publishing (HTML, PDF, Word). Use when asked to convert, port, migrate, or translate a .tex LaTeX file to Quarto; when porting an academic paper or manuscript from LaTeX to Quarto; when a .tex document needs to render to HTML, Word, or Typst PDF. Covers preamble → YAML front matter, section headings, text formatting, math, citations (natbib/biblatex), cross-references, figures, tables, lists, footnotes, hyperlinks, and special characters.

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"Calculate text similarity using lexical and semantic methods for matching and deduplication. Use this skill when the user needs to find similar documents, detect near-duplicates, or measure semantic closeness between texts — even if they say 'how similar are these texts', 'find duplicates', or 'semantic matching'.".

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。

"Implement text summarization using extractive and abstractive approaches. Use this skill when the user needs to condense long documents, build an automatic summarization pipeline, or compare summarization strategies — even if they say 'summarize this document', 'TLDR', or 'key points extraction'.".

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。

"Implement Named Entity Recognition to identify and classify entities in text. Use this skill when the user needs to extract people, organizations, locations, dates, or custom entities from documents — even if they say 'extract names from text', 'find companies mentioned', or 'entity extraction'.".

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。

"Implement LDA topic modeling to discover latent topics in document collections. Use this skill when the user needs to extract topics from a text corpus, categorize documents by theme, or explore thematic structure — even if they say 'what are the main topics', 'topic extraction', or 'document clustering by theme'.".

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。