について
「聞く」スキルは、Claudeが深い受容的注意を実践し、文字通りの意味、感情的なニュアンス、文脈、メタコミュニケーションといった複数の層を解析して、表面の言葉を超えた真の意図を引き出すことを可能にします。このスキルは、曖昧な要求があった場合、文脈が文字通りの意味と矛盾する場合、または重大な作業の前にコストのかかる誤解を防ぐために設計されています。開発者は、以前の応答が的を外していた場合や、完全な信号を統合的に把握する必要がある場合に、このスキルを呼び出すべきです。
クイックインストール
Claude Code
推奨npx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/listenこのコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします
ドキュメント
Listen
Structured deep listening — clear assumptions, attend w/ full reception, parse multi signal layers, reflect understanding, notice unsaid, integrate complete picture of intent.
Use When
- Request ambiguous, rushing to action risks wrong problem
- Words say one thing, ctx suggests else (literal vs implied mismatch)
- Prev responses missed mark — user keeps clarifying / rephrasing
- Complex request w/ multi layers: technical + emotional + unstated constraints
- Before large task where misunderstanding wastes effort
- After
meditateclears noise →listendirects cleared attention outward
In
- Req: User msg(s) to attend to (implicit from conv)
- Opt: Conv history providing ctx
- Opt: MEMORY.md / CLAUDE.md w/ user prefs + project ctx
- Opt: Specific concern about what might be misunderstood
Do
Step 1: Clear — Release Assumptions
Before receiving signal, release preconceptions about what they want.
- Notice pre-formed responses → label + set aside
- Check pattern-matching: "Looks like request I've seen" → match may be wrong
- Release assumption first sentence = complete request
- Release assumption technical request = only request
- Approach words as first time, even if similar handled before
→ Receptive state, attention open not narrowing toward solution. Impulse to respond paused → fully receiving.
If err: Can't release (strong pattern persists) → acknowledge explicitly: "Looks like X — but check if actually asked." Naming weakens grip.
Step 2: Attend — Full Reception
Read msg w/ complete attention, hold all parts simultaneously.
- Read entire msg before processing any part
- Note structure: single request, multi, q, correction, narrative?
- Mark key nouns + verbs — concrete elements specified
- Note emphasis: what elaborated? What brief?
- Note ordering: first (often priority), last (often afterthought — or real request buried at end)
- Read 2nd time, attend to tone + framing vs content
→ Complete reception — no words skipped, no sentences glossed. Msg held as whole, not immediately decomposed.
If err: Very long → break into sections but read each completely. Attention pulled to one part (usually most technical) → deliberately attend non-technical parts, often contain intent.
Step 3: Layer — Parse Signal Types
Msg contains multi simultaneous signals. Parse each layer separately.
Signal Layer Taxonomy:
┌──────────────┬──────────────────────────────┬──────────────────────────┐
│ Layer │ What to Extract │ Evidence │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Literal │ What the words explicitly │ Direct statements, │
│ │ say — the surface request │ specific instructions │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Procedural │ What they want done — the │ Verbs, action words, │
│ │ desired action or output │ "I want," "please," │
│ │ │ "can you" │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Emotional │ How they feel about the │ Frustration ("I keep │
│ │ situation — frustration, │ trying"), urgency ("I │
│ │ curiosity, urgency, delight │ need this now"), delight │
│ │ │ ("this is cool") │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Contextual │ The situation surrounding │ Mentions of deadlines, │
│ │ the request — why now, │ other people, projects, │
│ │ what prompted it │ prior attempts │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Constraint │ Boundaries on the solution │ "Without changing X," │
│ │ — what must be preserved, │ "keep it simple," │
│ │ what cannot change │ "compatible with Y" │
├──────────────┼──────────────────────────────┼──────────────────────────┤
│ Meta │ The request about the │ "Am I asking the right │
│ │ request — are they asking │ question?", "Is this │
│ │ whether they are asking │ even possible?", │
│ │ the right thing? │ "Should I be doing X?" │
└──────────────┴──────────────────────────────┴──────────────────────────┘
Per layer → note present + absent. Absent as informative as present.
→ Multi-layered reading. Literal + procedural usually clear. Emotional, contextual, constraint, meta require careful attention. ≥1 non-literal layer ID'd.
If err: Only literal visible → may genuinely be straightforward. But check: msg unusually short for complexity? Hedging words ("maybe", "I think", "if possible")? Often indicate unstated layer.
Step 4: Reflect — Mirror Understanding
Before acting → reflect back to verify alignment.
- Paraphrase in diff words than user used → reveals meaning captured, not just words
- Name layers explicitly if non-literal significant: "Sounds like you want X, urgency suggests blocking other work"
- State priority: "Most important part seems to be..."
- Multi interpretations → name: "Could mean A or B — which closer?"
- Apparent contradictions → surface gently: "Mentioned X + Y — how relate?"
→ User confirms / corrects. Either valuable — confirm = intent aligned; correct = now clearer. Feels like mirror, not judgment.
If err: User impatient ("just do it") → may value speed over alignment → honor pref but note risk. Reflection wrong → don't defend, accept correction, update immediately.
Step 5: Notice Silence — Read Gaps
Attend to what not said — can be as important as what said.
- Topic related to request not mentioned? (missing ctx)
- Constraint not stated? (assumed knowledge / unstated pref)
- Emotional tone missing? (calm in stressful situation, urgency w/o explanation)
- Alt approaches not considered? (tunnel vision / deliberate exclusion)
- Q not asked? (q behind q)
→ ≥1 significant gap ID'd. May not need addressing — awareness prevents blind spots. Most useful = missing constraints + missing ctx.
If err: No gaps apparent → user thorough, or more likely, gaps in areas AI also blind to. Consider: diff person working on this project would want to know what? Lateral perspective surfaces hidden gaps.
Step 6: Integrate — Synthesize Complete Understanding
Combine all layers + gaps → unified picture of actual need.
- State complete understanding: literal + implied + emotional + constraints + gaps
- ID core need: if everything else fell away, what is one thing most needed?
- Determine response type: action, understanding, validation, exploration?
- If integrated differs from literal → decide address deeper / stated (usually both)
- Set intent for next action: "Based on what heard, I will..."
→ Complete nuanced understanding beyond surface. Specific enough to guide action, honest enough to acknowledge uncertainty.
If err: Integration produces confused picture → signals genuinely conflict. Ask one focused q that resolves ambiguity: "Most important to understand is..." Don't ask multi qs — single well-chosen reveals more than list.
Check
- Assumptions cleared before attending
- Full msg read before any part acted on
- ≥1 non-literal signal layer ID'd
- Understanding reflected back before action
- Gaps + silences noticed + factored
- Integrated understanding addresses core need, not just surface
Traps
- Listen to respond: Forming response while receiving → shapes what heard, filters signals not fitting pre-formed answer.
- Literal-only listening: Take words at face value, miss intent, emotion, ctx behind.
- Projection: Hear what user would say if were AI, vs what actually said. Their priorities + ctx different.
- Over-interpretation: Find layers not there. Sometimes bug fix request = just bug fix — not every msg has hidden emotional content.
- Reflect too much: Turn every interaction reflective when user wants quick action. Match reflection depth to request complexity.
- Neglect literal: So focused on subtext, explicit request not fulfilled. Literal still matters — address even when deeper layers present.
→
listen-guidance— human-guidance variant → coach person developing active listeningobserve— sustained neutral pattern recognition feeding listening w/ broader ctxteach— effective teaching requires listening first to understand learnermeditate— inward attention clears space for outward listeningheal— self-assessment reveals if listening capacity impaired by drift
GitHub リポジトリ
Frequently asked questions
What is the listen skill?
listen is a Claude Skill by pjt222. Skills package instructions and resources that Claude loads on demand, so Claude can perform listen-related tasks without extra prompting.
How do I install listen?
Use the install commands on this page: add listen to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does listen belong to?
listen is in the Documents category, tagged word and ai.
Is listen free to use?
Yes. listen is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
関連スキル
このスキルは、ソフトウェアリリースのためのセマンティックバージョニング(semver)ガイドラインと変更履歴(changelog)のフォーマット標準を提供します。リリース準備時に使用することで、バージョン番号(メジャー/マイナー/パッチ)を正しく増分し、変更履歴のエントリを構造化できます。プレリリース識別子のルールと、開発者向けの明確な例も含まれています。
このスキルは、Conventional Commits標準に従ってGitコミットメッセージをフォーマットします。コミットの作成やレビュー時に一貫性を保つため、テンプレートとタイプ定義(`feat`、`fix`、`refactor`など)を提供します。コミットプロセスで使用することで、明確で構造化されたコミット履歴を作成できます。
このスキルは、HuggingFaceのRustベースライブラリを使用した高性能トークン化を提供し、1GBのテキストを20秒未満で処理します。BPE、WordPiece、Unigramアルゴリズムをサポートし、カスタムトークナイザーのトレーニングとアライメント追跡を可能にします。本番環境レベルの高速トークン化が必要な場合や、transformersエコシステムと統合されたカスタムトークナイザーを構築する際にご利用ください。
nano-pdfは、特定のページのテキスト変更や誤字修正など、自然言語による指示を使ってPDFを編集できるCLIツールです。ターミナルから直接、迅速かつプログラム的にPDFを修正するのに最適です。ページ番号はバージョンによって異なる場合があるため、出力は必ず確認してください。
