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listen

pjt222
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La habilidad "escuchar" permite a Claude practicar una atención receptiva profunda, analizando múltiples capas de comunicación —literal, emocional, contextual y meta— para extraer la verdadera intención más allá de las palabras superficiales. Está diseñada para solicitudes ambiguas, cuando el contexto contradice el significado literal, o antes de tareas importantes para evitar malentendidos costosos. Los desarrolladores deben invocarla cuando respuestas previas hayan errado el objetivo o cuando la señal completa requiera una integración holística.

Instalación rápida

Claude Code

Recomendado
Principal
npx skills add pjt222/agent-almanac -a claude-code
Comando PluginAlternativo
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternativo
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/listen

Copia y pega este comando en Claude Code para instalar esta habilidad

Documentación

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 meditate clears noise → listen directs 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.

  1. Notice pre-formed responses → label + set aside
  2. Check pattern-matching: "Looks like request I've seen" → match may be wrong
  3. Release assumption first sentence = complete request
  4. Release assumption technical request = only request
  5. 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.

  1. Read entire msg before processing any part
  2. Note structure: single request, multi, q, correction, narrative?
  3. Mark key nouns + verbs — concrete elements specified
  4. Note emphasis: what elaborated? What brief?
  5. Note ordering: first (often priority), last (often afterthought — or real request buried at end)
  6. 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.

  1. Paraphrase in diff words than user used → reveals meaning captured, not just words
  2. Name layers explicitly if non-literal significant: "Sounds like you want X, urgency suggests blocking other work"
  3. State priority: "Most important part seems to be..."
  4. Multi interpretations → name: "Could mean A or B — which closer?"
  5. 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.

  1. Topic related to request not mentioned? (missing ctx)
  2. Constraint not stated? (assumed knowledge / unstated pref)
  3. Emotional tone missing? (calm in stressful situation, urgency w/o explanation)
  4. Alt approaches not considered? (tunnel vision / deliberate exclusion)
  5. 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.

  1. State complete understanding: literal + implied + emotional + constraints + gaps
  2. ID core need: if everything else fell away, what is one thing most needed?
  3. Determine response type: action, understanding, validation, exploration?
  4. If integrated differs from literal → decide address deeper / stated (usually both)
  5. 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 listening
  • observe — sustained neutral pattern recognition feeding listening w/ broader ctx
  • teach — effective teaching requires listening first to understand learner
  • meditate — inward attention clears space for outward listening
  • heal — self-assessment reveals if listening capacity impaired by drift

Repositorio GitHub

pjt222/agent-almanac
Ruta: i18n/caveman-ultra/skills/listen
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

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