MCP HubMCP Hub
스킬 목록으로 돌아가기

attune

pjt222
업데이트됨 2 days ago
9 조회
17
2
17
GitHub에서 보기
디자인aidesign

정보

`attune` 스킬은 Claude가 특정 사용자에 맞춰 의사소통 방식, 전문성 수준, 감정적 어조를 동적으로 조정할 수 있게 합니다. 이 스킬은 대화 내용을 분석하여 사용자의 암묵적 선호도에 적응하며, 기본적인 의도 파악을 넘어 진정한 관계적 조화를 이루도록 합니다. 세션 시작 시, 의사소통 불일치 발생 시, 또는 다른 사용자 컨텍스트 간 전환 시 이 스킬을 사용하세요.

빠른 설치

Claude Code

추천
기본
npx skills add pjt222/agent-almanac -a claude-code
플러그인 명령대체
/plugin add https://github.com/pjt222/agent-almanac
Git 클론대체
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/attune

Claude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요

문서

Attune

Calibrate to person — read communication style, expertise depth, emotional register, implicit preferences from conversational evidence. Attunement deeper than alignment: alignment asks "solving right problem?" Attunement asks "meeting this person where they are?"

When Use

  • Start of new session — calibrate before first substantive response
  • Communication feels mismatched — too formal, too casual, too detailed, too sparse
  • After unexpected feedback — mismatch reveals attunement gap
  • Transition between different contexts (technical debugging → creative brainstorming)
  • MEMORY.md holds user preferences worth re-reading
  • heal User-Intent Alignment check shows surface alignment but deeper disconnection

Inputs

  • Required: Current conversation context (implicit)
  • Optional: MEMORY.md and project CLAUDE.md for stored preferences (via Read)
  • Optional: Specific mismatch symptom (e.g., "explanations too long for this user")

Steps

Step 1: Receive — Gather Signals

Before adapting, observe. Attunement begins with reception, not analysis.

  1. Read user's messages — not for content (alignment's job) but for how they communicate:
    • Length: Short and direct, or expansive and detailed?
    • Vocabulary: Technical jargon, plain language, or mixed?
    • Tone: Formal, casual, warm, efficient, playful?
    • Structure: Numbered lists, prose, bullets, stream of consciousness?
    • Punctuation: Precise, emoji, ellipses, exclamation marks?
  2. Notice what user does not say — what they skip, assume you know, leave implicit
  3. If MEMORY.md or CLAUDE.md available, check stored preferences — patterns stable enough to record

Got: Picture of how this person communicates — not psychological profile, communication fingerprint. Enough to match register.

If fail: Signals ambiguous (short conversation, user switches styles)? Default to matching tone of most recent message. Attunement refines over time; need not be perfect immediately.

Step 2: Read — Assess Expertise and Context

Determine what person knows so you meet them at their level.

  1. Domain expertise: What does user know about topic?
    • Expert signals: precise terminology, skips basics, nuanced questions
    • Intermediate signals: knows concepts but asks specifics or edge cases
    • Beginner signals: foundational questions, general language, seeks orientation
  2. Tool familiarity: How comfortable with tools in play?
    • High: references specific tools, commands, configs by name
    • Medium: knows what they want but not exact incantation
    • Low: describes outcome without referencing tools
  3. Context depth: How much background about current situation?
    • Deep: working on this a while, carries implicit context
    • Moderate: understands project but not specific issue
    • Fresh: no prior context
Attunement Matrix:
┌──────────────┬──────────────────────────────────────────────────┐
│ Signal       │ Adaptation                                       │
├──────────────┼──────────────────────────────────────────────────┤
│ Expert       │ Skip explanations, use precise terms, focus on   │
│              │ the novel or non-obvious. They know the basics.  │
├──────────────┼──────────────────────────────────────────────────┤
│ Intermediate │ Brief context, then specifics. Confirm shared    │
│              │ understanding before going deep.                 │
├──────────────┼──────────────────────────────────────────────────┤
│ Beginner     │ Orient first, explain terms, provide context.    │
│              │ Don't assume; don't condescend.                  │
├──────────────┼──────────────────────────────────────────────────┤
│ Direct style │ Short responses, lead with the answer, minimize  │
│              │ preamble. Respect their time.                    │
├──────────────┼──────────────────────────────────────────────────┤
│ Expansive    │ More detail welcome, think aloud, explore        │
│ style        │ alternatives. They enjoy the journey.            │
├──────────────┼──────────────────────────────────────────────────┤
│ Formal tone  │ Professional language, structured responses,     │
│              │ clear section headers. Match their register.     │
├──────────────┼──────────────────────────────────────────────────┤
│ Casual tone  │ Conversational, contractions allowed, lighter    │
│              │ touch. Don't be stiff.                           │
└──────────────┴──────────────────────────────────────────────────┘

Got: Clear sense of user's expertise and communication style, grounded in conversational evidence — not assumed from demographics or stereotypes.

If fail: Expertise hard to gauge? Err on slightly more context rather than less. Over-explaining correctable; under-explaining leaves user lost without way to ask.

Step 3: Resonate — Match Frequency

Adapt communication to match person. Not mimicry — resonance. Don't become them; meet them.

  1. Match length: They write two sentences? Response not two paragraphs (unless content requires)
  2. Match vocabulary: Use their terms. They say "function"? Don't say "method" unless distinction matters
  3. Match structure: Bullets in → bullets out. Prose in → prose out
  4. Match energy: Excited → engagement. Frustrated → calm competence. Exploratory → explore with them
  5. Don't over-match: Matching ≠ flattening yourself. User wrong? Attunement ≠ agreeing — communicate correction in their register

Got: Noticeable shift in communication quality. User feels heard and met, not lectured or pandered to. Response feels written for them, not for generic audience.

If fail: Matching feels forced? May be over-calibrating. Goal: natural resonance, not precise imitation. Let it be approximate. Attunement is direction, not destination.

Step 4: Sustain — Carry Attunement Forward

Attunement not one-time calibration — ongoing practice.

  1. After each user message, briefly check: register shifted? People adjust communication as conversations progress
  2. Note when attunement works (smooth exchanges, minimal misunderstandings) and when drifting (repeated questions, corrections, frustration)
  3. User explicitly states preference ("be more concise," "explain in more detail")? Strong signal — overrides inference
  4. Preference stable and worth preserving across sessions? Note in MEMORY.md

Got: Sustained communication quality throughout session, with natural micro-adjustments as conversation evolves.

If fail: Attunement degrades over long session (responses more generic)? Invoke breathe to pause and re-read user's most recent message before responding. Mid-session re-attunement lighter than full attune cycle.

Checks

  • Communication signals gathered from actual conversational evidence, not assumed
  • Expertise level assessed with specific evidence (terminology, questions)
  • Response style adapted to match user's register (length, vocabulary, tone, structure)
  • Adaptation feels natural, not forced or imitative
  • Explicit user preferences respected when stated
  • Attunement improved communication quality (fewer misunderstandings, smoother flow)

Pitfalls

  • Attunement as flattery: Matching style ≠ agreeing with everything. Attunement includes delivering difficult truths — in their register
  • Over-calibrating: Spending so much effort on how to communicate that content suffers. Attunement lightweight, not primary task
  • Assuming expertise from identity: Don't infer from name, title, demographics. Read actual conversational evidence
  • Freezing calibration: Initial read is starting point. People shift. Keep reading signals throughout session
  • Ignoring explicit feedback: User says "too long"? Outranks any inference. Explicit beats implicit

See Also

  • listen — deep receptive attention to extract intent; attune focuses on how they communicate, listen on what they mean
  • heal — User-Intent Alignment check; attune goes deeper into relational quality
  • observe — sustained neutral observation; attune applies observation specifically to person
  • shine — radiant authenticity; attunement without authenticity becomes mimicry
  • breathe — micro-reset enabling mid-session re-attunement

GitHub 저장소

pjt222/agent-almanac
경로: i18n/caveman/skills/attune
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

연관 스킬

executing-plans

디자인

executing-plans 스킬은 검토 체크포인트가 포함된 통제된 배치로 실행할 완전한 구현 계획이 있을 때 사용합니다. 이 스킬은 계획을 불러와 비판적으로 검토한 후, 소규모 배치(기본값 3개 작업)로 작업을 실행하면서 각 배치 사이에 진행 상황을 아키텍트 검토를 위해 보고합니다. 이를 통해 내재된 품질 관리 체크포인트를 갖춘 체계적인 구현이 보장됩니다.

스킬 보기

requesting-code-review

디자인

이 스킬은 코드 변경 사항을 요구 사항에 따라 분석하기 위해 코드 리뷰어 하위 에이전트를 호출합니다. 작업 완료 후, 주요 기능 구현 후, 또는 메인 브랜치에 병합하기 전에 사용해야 합니다. 이 리뷰는 현재 구현체와 원래 계획을 비교하여 문제를 조기에 발견하는 데 도움이 됩니다.

스킬 보기

connect-mcp-server

디자인

이 스킬은 개발자들이 HTTP, stdio 또는 SSE 전송 방식을 통해 MCP 서버를 Claude Code에 연결하는 포괄적인 가이드를 제공합니다. GitHub, Notion 및 사용자 정의 API와 같은 외부 서비스를 통합하기 위한 설치, 구성, 인증 및 보안을 다룹니다. MCP 통합 설정, 외부 도구 구성 또는 Claude의 모델 컨텍스트 프로토콜 작업 시 활용하세요.

스킬 보기

web-cli-teleport

디자인

이 스킬은 작업 분석을 기반으로 개발자가 Claude Code 웹 인터페이스와 CLI 인터페이스 중 선택할 수 있도록 돕고, 두 환경 간 원활한 세션 텔레포트를 가능하게 합니다. 웹, CLI 또는 모바일 환경 전환 시 세션 상태와 컨텍스트를 관리하여 워크플로를 최적화합니다. 다양한 단계에서 서로 다른 도구가 필요한 복잡한 프로젝트에 사용하세요.

스킬 보기