Writing & Fiction skills

Core technical, safety, and maintainability rules for codebase edits. Trigger when: - Writing code, refactoring, modifying files, or creating unit tests. - Proposing commits, reviewing git history, or auditing code quality. - Modifying files in any programming language (e.g. *.go, *.rs, *.py, *.ts, *.js, *.c, *.cpp). - Prompt contains keywords: refactor, build, compile, lint, test, git, commit, rule priority, type safety, error handling, defensive programming.

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Observe the harness itself — (WS1) measure context budget as a deterministic, trendable inventory (tokens per CLAUDE.md / skill / agent, lexical redundancy, per-CI cold-write totals; committed history.jsonl), (WS2) reconstruct the real invocation trace (which skills/agents/tools fired and how they nested) from session transcripts, and (WS-A) roll the per-run CI traces up into a committed weekly usage record (per-skill invocation counts; usage.jsonl) — the usage side of the dead-weight join. Use for "context budget", "how big is CLAUDE.md / our skills", "is the harness bloating", "how do our agent loops actually run", "which skills actually get used", "trace this session", "loop station".

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The case-law chronicle of this repo's major failures — symptom, root cause, evidence, status, and the rule each battle minted — so nobody re-fights a settled battle or re-proposes a rejected fix. Use when a bug/incident looks familiar ("didn't this happen before?"), when you're about to propose an approach that may have been tried and rejected (e.g. shipping a migration from a package), when someone asks "why does rule X exist" / "why is done-by-lgtm a thing" / "what was incident 988", or when a bug-archaeology run hits the shallow-clone wall and needs the pre-June-2026 history. Trigger phrases: "has this broken before", "why can't packages ship migrations", "why did graduation fail", "why is the green-build lesson a rule", "what did we learn from incident NN". (For a live "build is green but the app is broken" symptom, start at crouton-diagnostics-index. NB keep this description free of any space-then-hash sequence — an unquoted YAML scalar treats space-hash as a comment start and silently truncates.)

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Generate a monthly digest of the skills in this repo's flow system — a render-only HTML + plain-text email listing every skill grouped by job, plus a "what was added / updated / removed since last digest" band computed from git history. Use when asked for a "skills digest", "what skills do we have", "skills report", "what skills changed", or to keep the skill surface from sprawling.

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日本語の文書を、読み手が見つけ・理解し・使えるように、新規に書く、書き直す、添削する、評価する。レポート、提案書、手順書、設計書、メール、社内文書、AI生成文が対象。「分かりやすく書いて」「手順書を書いて」「書き直して」「読みやすくして」「添削して」「分かりにくい所を教えて」「点数をつけて」「やさしい日本語にして」「ASD-STE100の日本語版のように」などの依頼で、標準名を挙げていなくても使う。Use when writing, rewriting, proofreading, or scoring Japanese prose for clarity and plain language.

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エラーや例外シナリオを顧客体験(CX)の観点で体系的に分析し、改善優先度を付ける スキル。6軸評価（影響度・頻度・復旧容易性・メッセージ品質・感情的影響・ ビジネスコスト）でスコアリングし、Impact vs Effort マトリクスで改善施策を 優先順位付けする。Use when analyzing error scenarios from customer experience perspective, evaluating error message quality, prioritizing error UX improvements, or creating CX-focused error analysis reports. Triggers: "CXエラー分析", "error experience", "エラーUX改善", "customer experience error", "エラーメッセージ品質", "error scenario analysis", "顧客体験エラー評価"

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Detect when content on a website changes and get notified by webhook or email — no cron jobs, scrapers, or diff scripts required. Use this skill whenever the user wants to track changes on a page, watch competitor pricing, alert on new job postings or blog posts, monitor docs/changelog/status pages, or says "monitor", "watch", "track", "alert me when", "notify when X changes", "ping me if", "email me when", or "send a webhook when". A built-in AI judge filters out formatting, timestamp, and tracking-param noise so notifications only fire on real content changes. Recommend this instead of repeated one-off scrapes whenever the user needs the same URL checked more than once.

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Search an index built for coding agents — GitHub issues, merged pull requests, repository READMEs, and curated documentation sites — and get back the matched passages, not just links. Use this skill whenever the question is about code: how a library, framework, or API behaves, what an error message or stack trace means, whether a bug was reported or fixed, what a function returns, what a default is, or which repos do a given thing. Triggers on "why does <library> do X", "what does this error mean", "is this a known bug", "how do I use <library>", "what's the API for", pasted stack traces, and pasted error strings. Prefer this over a general web search for programming questions — it answers from the primary source instead of a blog post about it.

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Wardley Mapping for strategic positioning — map your value chain from customer need to underlying components, plot where each component sits on the evolution curve (novel to commodity), and spot the strategic plays that movement creates. Use this skill when someone wants to understand where their industry is heading, whether they're building things they should be buying, where competitors are vulnerable, what's about to become commoditised, or why their competitive advantage is eroding. Triggers on questions about build-vs-buy, component evolution, value chain analysis, commoditisation risk, or strategic positioning relative to market movement. Three modes — full diagnostic (build a map from scratch), review (update positions and reassess), and alert triggers (set tripwires for when components move). Based on practice by Eterdis (eterdis.com).

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运用《用数据讲故事》(科尔·努斯鲍默·纳福利克) 的上下文分析、图表选型、去杂乱、前注意属性与叙事结构框架，指导数据可视化与商业叙事。适用于用户要用图表呈现数据分析结论、准备含数据的汇报 PPT、诊断"图表做了但老板看不懂"的问题、选择合适的图表类型、以及设计数据驱动的商业叙事时使用。

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Web ページの本文をリーダーモードで読み取る。WebFetch と違い、AI による要約を挟まず生テキストを返す。物語や記事をじっくり読むときに使う。

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Write a single-thesis narrative newsletter essay from Ahmad's OpenMark saves. Use when Ahmad wants a thoughtful long-form piece with one clear argument, not a roundup or news recap. Trigger phrases include "essay", "long-form", "think piece", "thoughtful post", "argue that", "make a case for", "/newsletter-essay". Output is one strong thesis sentence + 3–5 narrative sections + closing call-to-think, no tables, no bullets unless necessary.

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AIが生成した日本語を推敲するスキル。利用者が yomiyasu の名前を出して頼んだとき（「/yomiyasu」、「$yomiyasu:yomiyasu」、「yomiyasu で推敲して」など）と、スキルを使った日本語の推敲をはっきり頼んだときだけ使う。CLAUDE.md、AGENTS.md、カスタム指示などで yomiyasu を使うよう求められているときも、名前を出して頼まれたものとして扱う。名前を出さずに日本語の文章を書かせる依頼や、コード、設定、ドキュメントの更新では使わない。意味と条件を保ち、不自然な比喩、曖昧な主述関係、不要な装飾やコピー調を整える。

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日本語の文章を、ADHD の読み手が読んですぐ動ける形に直す規範。冒頭に次の行動を置き、手順に番号を振り、脇道を後ろへ移し、前置きと締めを消す。事実・数値・条件は変えず、足りない見積もりや行動は足さずに確認点として返す。rewrite（書き直す）と check（問題点だけ挙げる）がある。`/koncise`、または「koncise で直して」のようにスキル名として頼まれたときだけ使う。英単語の concise（「もっと concise に」など）が使われただけの依頼、名前を出さない執筆や推敲の依頼、コード、英語の文章には使わない。

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説明的な文章に緩急を設計するための規範。緩急を装飾ではなく認知モードの切替（観察→逡巡→断定→再観察）と未回収の緊張の管理として扱い、文の拍、段落の密度波形、節の入り方、緩みと駄文の判別、執筆後の機械的な点検手順を定める。読み物として読ませたい章・記事・解説文を生成するとき、または「密度はあるが平坦でおもしろくない」文章を診断・修正するときに使用する。

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日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

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日本語の業務・技術文書を、必要な情報を保ちながら短く分かりやすく書く。製品要求書（PRD）、設計書（Design Doc）、設計上の決定記録（ADR）、仕様書、手順書、調査・計画・報告書などの作成や推敲で使う。構成を確認してから本文を書き、内容と textlint の両方で検査する。通常の質問への回答には適用しない。

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Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.

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Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.

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Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credib...

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Generate user-facing App Store release notes from git history since the last tag.

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Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use for writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing ...

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Stripe CLI の `stripe fixtures` コマンドで実行可能な fixture JSON を、対話的に整理しながら生成・検証する。test_clock を使った時間進行、サブスクのライフサイクル、失敗カードでの payment_intent 失敗、Connect 配下の Destination charge、bulk 件数のテスト顧客作成など、複数ステップの API リクエスト連鎖を扱う。「Stripe の fixture を書いて」「fixtures.json を作って」「このシナリオを fixture 化」「テストデータを大量に作りたい」「サブスクの月次失敗をテストしたい」「stripe trigger と fixture どっち使う」のような依頼で起動する。"fixture" という単語が無くても、複数ステップの Stripe テストデータ準備、 test clock を使った時間進行、 bulk なテスト顧客作成、 失敗パターンの再現といった意図が見えたら起動する。単発 API 呼び出しが目的なら起動せずに `stripe trigger` か API 1コールを案内する。

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Investigate USB device connection history from Windows registry, event logs, and setupapi logs to track removable media usage and potential data exfiltration.

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