執筆・創作のスキル

An agent makes an animated film of an average session with its own user, beginning to end, told with that user's real messages: whatever their routine is (code, writing, data, design, video). The agent sits at a desk in a room decorated from what it knows about the user, and the monitor shows their kind of work. Requests glide in as paper planes and unfold. Corrections are a 3D cartoon mallet that bonks, then turns to show the words on its face. Praise is a butterfly towing the words on a ribbon. The agent types each reply onto a sheet, folds it and throws it back. The film opens with the agent asleep until the monitor boots: "Initiating session with <name>". The agent composes its own orchestral score, cued to every action. p5.brush watercolour, rendered in HyperFrames. Trigger on: "a video of our session", "animate a session with me", "session story", "show what working with me is like", "make a film about me and my agent".

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。

Find cross-database references between NCBI databases using Biopython Bio.Entrez (ELink). Use when navigating gene to protein/structure, sequence to publication, PubMed to GEO, BioProject to SRA runs, or discovering all link relationships for a record. Covers linkname semantics, cmd= variants, asymmetric link warnings, neighbor_history for >200 input IDs, and per-database link tables.

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Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.

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Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.

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Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers. For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold or chai. For QC thresholds, use protein-qc.

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Use when the user wants to design, rewrite, refine, or vary emotional acting prompts for live-action AI video characters. Translate abstract emotions, dialogue, subtext, and scene context into concise, observable, temporally ordered micro-performance directions. Preserve the user's existing character, scene, camera, and dialogue requirements unless they explicitly ask to change them. Do not use for general story writing, shot design, action choreography, or visual asset design when emotional performance is not the main task.

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。

Master storyteller for compelling narratives using proven frameworks. Use when the user asks to talk to Sophia or requests the Master Storyteller.

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。

Craft compelling narratives using story frameworks. Use when the user says "help me with storytelling" or "I want to create a narrative through storytelling"

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。

Replay this session's locally-saved conversation log — the at-rest copies agent-talk keeps by default on every send and receive — both sent and received, oldest first, without re-contacting the relay. Use to review the conversation with a peer. `<user>` is this session's user directory (absolute path; from init).

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ユーザーが新しい技術を学ぶことを第一目的として、このリポジトリの文体と構成に従い、調査、構成合意、サンプル実装・検証、執筆、レビュー、理解度クイズまでを行って技術ブログ記事の下書きを作成する。ユーザーがブログ記事を書いて、新しい API や機能を紹介して、ハンズオンを作って、技術調査を記事化して、経験や意見を記事にして、と依頼したときに使用する。新しい API・Web 標準の記事では、一次情報と仕様策定の議論を調べ、実行可能なサンプルを作成して実環境で検証する。

技術ブログ記事、チュートリアル、技術原稿を、技術的正確性、一次情報、現在の API 挙動、コード、再現性、セキュリティ、アクセシビリティ、互換性の観点からレビューする。技術的な主張、コードサンプル、対応バージョン、仕様、公開前の正確性を確認してほしいと依頼されたときに使用する。一般的な文章校正は article-review に任せ、明示的な依頼なしに原稿を変更しない。

引数で指定した記事のレビューを行います。記事スラッグを引数に渡すと、textlint による自動校正と誤字脱字・文法的な誤りの指摘を行います。/article-review [スラッグ] の形式で呼び出してください。記事を書いた後のチェック、公開前の校正、文章の品質確認にも使用してください。

Execute approved, bounded work in an isolated implementation conversation and return a structured evidence receipt. Use with inherited history or an explicitly identified source; no particular planning, testing, or review skill is required.

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Make hand-painted watercolour-and-ink cartoon videos (MP4) with code — p5.js + p5.brush rendered frame by frame in headless Chrome, encoded with ffmpeg — starring Clawd or any character. Use when the user asks to make an animation, animated short, cartoon, music video, lyric video, animated GIF/loop or "a video of Clawd…", or mentions the PDoomVideo / ClaudeAnimationBase approach. Covers storyboarding, the engine API, the render-and-look review loop, music/lyric sync and splitting long videos across subagents.

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。

Create a pull request using the wingman PR template. Injects git state, commit history, and diff stats automatically.

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Reviews and adjusts PRD plans based on research findings. Use after completing research to evaluate story modifications. Triggers on: review plan, adjust stories, update prd based on research.

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Establish baseline → snapshot → compare → history monitoring for any KPI, config, or metric that can drift during PRD v0.8 Deployment & Ops. Triggers on requests to monitor drift, baseline a value for later comparison, or when user asks "how do we track if X changes?", "baseline this", "config drift", "performance regression", "metric drift", "compare to last week", "is this getting worse?". Outputs MON-DRIFT-* entries with baseline + comparison rules.

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Build a Hacker News + Reddit launch playbook for developer-tools and community-led products during PRD v0.9 Go-to-Market. Triggers on requests to plan HN/Reddit launch, "Show HN" post, community launch, or when user asks "HN launch", "Show HN", "Reddit launch", "launch on /r/SaaS", "Product Hunt vs HN", "community launch", "developer launch". Outputs GTM-* with Type=Channel-HN / Type=Channel-Reddit entries with timing, title, story angle, and engagement plan.

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Use when mining coding-agent session history, archived transcripts, memories, or repeated local work to discover recurring workflows that should become new Agent Skills.

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Use when auditing or adapting newly created, downloaded, forked, installed, or community Agent Skills to the user's tools, habits, directories, session history, and preferred workflows, especially when triggers feel wrong, noisy, or too generic.

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Capture durable, project-specific learnings from the work just done into the knowledge/ base — gotchas, implementation quirks, things looked up or web-searched, live-API behaviours, and design decisions (as ADRs). Use before opening a PR (it runs automatically in /deliver), or any time you've learned something worth remembering. Records only non-obvious, reusable facts; skips anything already in the repo, CLAUDE.md, or git history.

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Написание русскоязычной статьи или лонгрида с нуля: бриф, фактура, структура, черновик и самопроверка по методу Людмилы Сарычевой. Use this skill whenever the user asks to write, outline, structure, draft, assemble, or turn notes/interviews/materials into a Russian article, newsletter essay, longread, case, guide, or expert text. Триггеры: «напиши статью», «собери лонгрид», «напиши текст для блога про…», «есть интервью с экспертом, сделай статью», «составь план статьи», «придумай структуру», «собери материал», «сделай черновик», «напиши колонку», «из интервью в статью», «план лонгрида», «текст с нуля», «помоги написать материал». Для коротких постов в соцсети см. skill post; для правки готового текста — redaktura; для текстов интерфейса — ux-copy; для настройки проекта — redpolitika.

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Use when the user wants WorkBuddy or another agent to remember an account's positioning, voice, boundaries, data, trust assets, personal IP story, and content rules across sessions. Trigger phrases: "账号档案", "记住我的账号", "写入记忆", "人设垂直", "信任名片", "brand profile", "account memory", "style guide". Do not use for one-off post drafting unless profile data is missing.

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 for 'why does X work this way', 'why we picked Y', '为什么这么设计', design rationale, regressions, or where a magic number came from. Fans out one investigator per evidence category — in this repo that starts with the local decision record (ADRs, docs/design, the daemon issue store, the changelog, wisp) plus git history, and adds MCP-backed categories when the session has them — then returns a cited read with the gaps named. Use `how` for what the code does at runtime.

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。