297 件 ・ 関連度順
概要と使いどころ
Use this skill when reviewing, designing, or improving a workshop, lesson, training session, facilitation plan, talk, or educational explanation. Use it when the user provides a topic, concept, or explanation and wants better framing questions, curiosity hooks, opening prompts, discussion questions, learner reflection prompts, or ways to make participants think before being taught.
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 generating visual artifacts — explanations, diagrams, slides, or diff visualizations. Triggers on "explain X visually", "diagram this", "show as slides", "diff against main". NOT for rendering a plan as HTML (see mk:visual-plan), live media generation (see mk:multimodal), browser QA (see mk:qa), or plan critique (see mk:plan-ceo-review).
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 answering factual or explanatory questions about the current project — codebase, architecture, conventions, workflows, constraints — with minimal cited evidence. Triggers on "how does X work here", "what does X mean", "why is X structured this way", "is this claim true in the repo", "explain X with sources". NOT for brainstorming or comparing approaches (mk:brainstorming), trade-off decisions (mk:party), debugging/root cause (mk:investigate), code review (mk:review), plans (mk:plan-creator), security audits (mk:cso), visual explanations/diagrams (mk:preview --explain), test-coverage gaps (mk:nyquist), library docs (mk:docs-finder), or workflow navigation (mk:help).
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。
Explain a topic like I'm a 5 year old, as a single HTML artifact built from big pictures and very few words. Use this whenever the user asks for a dead-simple explanation of how something works, says "ELI5", "explain like I'm five", "簡単に説明して", "図で説明して", "初心者向けに", "素人にもわかるように", wants to explain a concept to a non-technical manager, customer, or family member, or asks for a visual explainer — even if they don't say "ELI5" explicitly.
Use this skill when writing or editing Japanese documentation, teaching material, comments, or explanations for this template (Sabakyan style). Trigger words: ドキュメント執筆, 教材, 解説を書く, 日本語スタイル, README 作成, 説明文, サバキャン, わかりやすく書く.
Generates Nano Banana Pro prompts for technical explanation infographics. Use when user mentions "図解作成", "テック図解", or "AI解説図".
Help the user understand the current topic visually with concise diagrams, code-shape sketches, and focused HTML artifacts. Use when the user asks to show / diagram / visualize / sketch / illustrate what is going on, asks "what does this look like", "how does this flow", "show me the structure", or in Japanese 図で見せて / 図解して / 図にして / 構造を見せて / フローを見せて / 全体像を見せて / どうつながってるか見せて. Also use it proactively when an explanation is running long and a call tree, file tree, component tree, diff, Mermaid diagram, or a small HTML artifact would land faster than prose.
Improve, rewrite, and explain workplace English for an English-as-a-second-language professional in Australia. Use when the user asks to polish, fix, rewrite, improve, or check work emails, Slack or Teams messages, follow-ups, replies to managers or stakeholders, technical explanations, status updates, polite chasing messages, questions, pushback, issue explanations, or similar workplace communication for Australian companies. Ask targeted clarifying questions before rewriting when the intended meaning, recipient, action, deadline, blame, commitment, or technical conclusion is unclear.
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。
Write or edit Japanese articles, reports, guides, and public-facing drafts so the argument is clear and the prose reads naturally. Preserve the author's meaning, evidence, and voice when revising. Use for requests to write from a topic or notes, remove AI臭 / AIっぽさ, improve awkward wording or structure, or format notes as 箇条書き, チーム共有, 社内共有, a decision note, handoff, Slack post, or Teams post. For existing prose, ask Gemini through Antigravity CLI to rewrite naturally by default, then audit against the source; use the current model if unavailable. Do NOT use for ordinary Japanese answers, progress updates, technical explanations, code review, English-only prose that is not a bullet-formatting request, or an explicitly incompatible format.
Explains ML predictions on omics data with SHAP, LIME, and permutation importance, handling the correlated-feature trap, the conditional-vs-interventional Shapley choice, and the attribution-is-not-causation boundary. Use when interpreting an omics classifier, debugging shortcut/batch learning, or deciding whether an attribution ranking can be trusted as biology. For validated feature selection see machine-learning/biomarker-discovery; explanations are not a selection method.
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。
動作確認やPR用の録画に字幕、注目箇所のズーム、再生速度の変更を加え、元動画を証拠として残しながら説明付きのMP4に仕上げるスキル。
バグやテスト失敗、予期しない動作の原因を、再現手順やログ、直近の変更から調べます。仮説の検証から修正後のテストまで、根拠に沿って進めるスキルです。
集めた素材から記事の展開を複数提案し、選んだ内容を一段ずつ書き進めます。読者が知っている概念を確認し、必要な説明を先に置きながら文章を組み立てるスキルです。
Govern stable domain context with a narrowly scoped CONTEXT.md when needed, and route hard-to-reverse decisions to ECC's existing architecture-decision-records skill. Use when domain terms require repeated explanation, one term has multiple meanings, unclear language causes module-boundary mistakes, or domain semantics must remain separate from architecture decisions.
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。
回答前に詳しさを4段階で選び、文章量の目安となるトークン数を確認するスキル。短い結論から詳細な解説まで、選んだ水準に合わせて回答を調整します。
AIへの依頼文から目的や不足情報を整理し、作業範囲に合うECCのコマンドやスキルを提案します。診断と改善理由を添え、そのまま貼り付けて使える依頼文に書き直します。
技術や設計を選んだ理由を、背景・比較案・影響とともにMarkdownへ記録するスキル。連番と索引で整理し、既存の記録から過去の判断理由も確認します。
実在するファイルや行番号を参照した段階的なコード案内をCodeTour形式で作成し、新任者の学習、設計の理解、PRレビュー、障害原因の調査に役立てるスキル。
色・文字・余白などのデザイン値と使い方をDESIGN.mdにまとめます。構造や配色のコントラストを検証し、変更比較やTailwind向けの書き出しまで支援するスキルです。
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
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 you need a deep-dive explanation of a specific file, function, or module in the codebase
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。
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
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。
Load the body before the first implementation edit for a bug fix or behavior change, or when the user or governing specification makes reusable tests a deliverable. It keeps the smallest focused test with the delivered project and updates coverage when behavior changes. Do not load for greenfield work unless reusable tests are explicitly required, behavior-preserving refactors, verification-only work, plan/review/explanation/documentation/formatting/generated-output-only work, explicit no-change or no-tool work, or when the user declines tests.
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。
For use only in threads for this proactive personal assistant. Investigate software issues; inspect, write, review, or test code; work on a repository or local engineering file; or create, fix, or monitor a pull request or CI run. Use for actual engineering or product QA work, not a general programming explanation.
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。