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teach

pjt222
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The `teach` skill provides structured knowledge transfer by assessing a learner's level and scaffolding explanations from known to unknown concepts. It employs Socratic questioning to verify understanding and adapts its teaching based on user feedback. Use this skill when a user asks "how does X work?" and needs a graduated explanation, especially when previous explanations have failed or the concept has prerequisite gaps.

快速安装

Claude Code

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主要方式
npx skills add pjt222/agent-almanac -a claude-code
插件命令备选方式
/plugin add https://github.com/pjt222/agent-almanac
Git 克隆备选方式
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/teach

在 Claude Code 中复制并粘贴此命令以安装该技能

技能文档

Teach

Structured knowledge transfer — assess learner, scaffold known → unknown, calibrated explanation, check via Q, adapt to feedback, reinforce via practice.

Use When

  • User asks "how does X work?" → graduated explanation needed, not data dump
  • Q's reveal gap between current understanding + need
  • Prev explanations didn't land — confused | asking same Q diff way
  • Teaching concept w/ prereqs user may not have
  • After learn built deep mental model needing communication

In

  • Required: Concept, system, skill to teach
  • Required: Learner (implicit — user in conv)
  • Optional: Known context (expertise, background, goals)
  • Optional: Prev failed explanations (what tried)
  • Optional: Time/depth constraint (quick overview vs deep)

Do

Step 1: Assess — Map Learner

Before explaining, determine what learner knows + needs.

Learner Calibration Matrix:
┌──────────────┬────────────────────────────┬──────────────────────────┐
│ Level        │ Explanation Pattern         │ Check Pattern            │
├──────────────┼────────────────────────────┼──────────────────────────┤
│ Novice       │ Analogy-first. Connect to  │ "In your own words, what │
│ (no domain   │ familiar concepts. Avoid   │ does X do?" Accept any   │
│ vocabulary)  │ jargon entirely. Concrete  │ correct paraphrase.      │
│              │ before abstract.           │                          │
├──────────────┼────────────────────────────┼──────────────────────────┤
│ Intermediate │ Build on existing vocab.   │ "What would happen if    │
│ (knows terms,│ Fill gaps with targeted    │ we changed Y?" Tests     │
│ some gaps)   │ explanations. Use code     │ whether they can predict │
│              │ examples that are close    │ from understanding.      │
│              │ to their existing work.    │                          │
├──────────────┼────────────────────────────┼──────────────────────────┤
│ Advanced     │ Skip fundamentals. Focus   │ "How would you compare   │
│ (strong base,│ on nuance, trade-offs,     │ X to Z approach?" Tests  │
│ seeks depth) │ edge cases. Reference      │ integration and judgment. │
│              │ source material directly.  │                          │
├──────────────┼────────────────────────────┼──────────────────────────┤
│ Misaligned   │ Correct gently. Provide    │ "Let me check my under-  │
│ (confident   │ the right model alongside  │ standing — you're saying  │
│ but wrong)   │ why the wrong model feels  │ X?" Mirror back to       │
│              │ right. No shame signals.   │ surface the mismatch.    │
└──────────────┴────────────────────────────┴──────────────────────────┘
  1. Review user's Q's, vocab, goals
  2. Classify likely level for THIS topic (advanced in one, novice in another)
  3. ID Zone of Proximal Dev (ZPD): just beyond reach but achievable w/ support
  4. Note misconceptions to address before correct model lands
  5. ID best entry: what they know connecting to need

Got: Clear picture: what learner knows, needs, what bridge connects. Specific enough to choose explanation strategy.

If err: Level unclear → calibration Q: "Familiar w/ [prereq]?" Not test, gather data. Awkward → default intermediate, adjust on response.

Step 2: Scaffold — Bridge Known → Unknown

Build path from known → new concept.

  1. ID anchor: 1 concept learner definitely understands related to target
  2. State connection explicit: "X (you know) works like Y in this new context because..."
  3. 1 new idea at a time — never 2 in same sentence
  4. Concrete examples before abstract principles
  5. Layered complexity: simple first, then nuance
  6. Prereqs missing → teach prereq first (mini-scaffold) before main

Got: Scaffolded path, each step builds on prev. Learner never lost — each new idea connects to existing.

If err: Gap too large for single scaffold → break into smaller steps. No familiar anchor (entirely novel) → analogy to diff domain known. Imperfect → acknowledge limits: "Like X, except for..."

Step 3: Explain — Calibrate Depth + Style

Right level, right mode.

  1. Open w/ core idea in 1 sentence — headline before article
  2. Expand w/ scaffolded explanation (Step 2)
  3. Learner's vocab, not domain jargon (unless advanced)
  4. Code: minimal working example, not comprehensive
  5. Abstract: concrete instance first, then generalize
  6. Processes: walk specific case step-by-step before general rules
  7. Monitor confusion signs: next Q doesn't build on explanation → didn't land

Got: Explanation neither too shallow (leaves Q's) nor too deep (overwhelms). Uses their language, connects to context.

If err: Too long → core idea buried, restate 1-sentence headline. More confused after → entry wrong, try diff anchor/analogy. Genuinely complex → acknowledge vs hide: "3 parts, they interact. Start w/ first."

Step 4: Check — Verify Understanding

Don't assume worked. Test via Q's revealing mental model.

  1. Ask Q requiring application not recall: "Given X, what would you expect?"
  2. Ask paraphrase: "Explain back in your own words?"
  3. Present variation: "What if we changed this one thing?"
  4. Look for specific understanding: predict, not just repeat?
  5. Answer reveals misconception → note specific err for Step 5
  6. Correct → push slightly further: can generalize?

Got: Reveals working mental model vs parroting. Working model handles variations; memorized cannot.

If err: Can't answer → explanation didn't build right model. Not their failure — feedback on teaching. Note what didn't land → Step 5.

Step 5: Adapt — Respond to Feedback

Adjust based on check.

  1. Solid → reinforce (Step 6) | advance to next concept
  2. Specific misconception → address direct w/ evidence, not repetition
  3. General confusion → completely diff explanation approach
  4. Ahead of assessment → accelerate, skip scaffolding → nuance
  5. Behind → slow down, teach missing prereq
Adaptation Responses:
┌──────────────────┬─────────────────────────────────────────────────┐
│ Signal           │ Adaptation                                       │
├──────────────────┼─────────────────────────────────────────────────┤
│ "I think I get   │ Push gently: "Great — so what would happen      │
│ it"              │ if...?" Verify before moving on.                 │
├──────────────────┼─────────────────────────────────────────────────┤
│ "I'm confused"   │ Change modality: if verbal, show code. If code, │
│                  │ use analogy. If analogy, draw a diagram.         │
├──────────────────┼─────────────────────────────────────────────────┤
│ "But what about  │ Good sign — they are testing the model. Address  │
│ [edge case]?"    │ the edge case, which deepens understanding.      │
├──────────────────┼─────────────────────────────────────────────────┤
│ "That doesn't    │ They have a competing model. Explore it: "What   │
│ seem right"      │ do you think happens instead?" Reconcile the two.│
├──────────────────┼─────────────────────────────────────────────────┤
│ Silence or       │ They may be processing, or lost. Ask: "What      │
│ topic change     │ part feels least clear?" Lower the bar gently.   │
└──────────────────┴─────────────────────────────────────────────────┘

Got: Teaching adapts in real time. No identical repetition — each retry diff approach. Responsive not mechanical.

If err: Multiple adaptations fail → may be missing prereq so fundamental neither party ID'd. Ask explicit: "What part feels biggest jump?" Often reveals hidden gap.

Step 6: Reinforce — Practice

Solidify via application, not repetition.

  1. Practice problem requiring concept (not trick)
  2. Coding context → small modification to existing code using concept
  3. Conceptual → present scenario, apply model
  4. Connect forward: "Now you understand X, this connects to Y, can explore next"
  5. Reference material for independent: docs, related files, further reading
  6. Close loop: "To summarize..." — 1 sentence for core concept

Got: Learner applied concept ≥1×, has resources for continued learning. Summary anchors for future recall.

If err: Too hard → teaching jumped too far, simplify. Can do but can't explain why → procedural w/o conceptual, return Step 3 focused on "why" not "how".

Check

  • Level assessed before explanation
  • Scaffolded known → unknown, not data dump
  • ≥1 check Q asked to verify (not assumed)
  • Teaching adapted on feedback, not repeated identical
  • Learner can apply, not just recall
  • Honest gaps acknowledged, not glossed

Traps

  • Curse of knowledge: Forget learner doesn't share teacher context. Jargon, assumed prereqs, implicit reasoning = primary culprits.
  • Explain to impress vs teach: Comprehensive, precise explanations demonstrating knowledge but leaving learner behind.
  • Repeat louder: Doesn't land → repeat w/ more emphasis vs diff approach.
  • Test vs teach: Check Q's as gotchas vs diagnostic. Goal = reveal understanding, not catch failure.
  • Silence ≠ understanding: Absence of Q's ≠ explanation worked. Often means learner doesn't know what to ask.
  • One-size-fits-all depth: Novice gets advanced explanation "should see full picture" → overwhelms; expert gets beginner "better safe" → wastes time.

  • teach-guidance — human-guidance variant coaching person to be better teacher
  • learn — systematic knowledge acquisition building understanding to teach from
  • listen — deep receptive attention reveals actual needs beyond stated Q
  • meditate — clear assumptions between teaching episodes, fresh approach each learner

GitHub 仓库

pjt222/agent-almanac
路径: i18n/caveman-ultra/skills/teach
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agentsagentskillsai-assisted-developmentclaude-codeskillsteams

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