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Methodology extract

Skill fagemx/prismstack/skills/methodology-extract

Turn your domain expertise into a runnable AI skill system — 10 principles, 6 pipeline patterns, 15D quality rubric. One beam of light in, a spectrum of skills out.

Install
npx -y skills add fagemx/prismstack --skill methodology-extract

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從用戶的材料、代碼、經驗中提取領域方法論。帶著用戶的問題看任何材料,提取對問題有用的原則。 不是被動整理材料(那是 /source-convert),是主動帶著 A 問題看 B 材料。 Trigger: 用戶說「這個可能有用」、「去看看這個」、「我覺得...」、「幫我整理方法論」、 「整合團隊的材料」、「合併大家的 prompt」、 或用戶帶來材料但不是要直接轉成 skill,而是想提取更高層的方法論。 Do NOT use when: 用戶明確說「把這篇轉成 skill」(用 /source-convert)。 Do NOT use when: 用戶要規劃 skill map(用 /domain-plan)。 上游:用戶的問題 × 任何材料。 下游:/domain-plan(映射成 skill map)或 /domain-build(生成 skill 時參考)。 產出:collisions/*.md + domain-methodology.md

SKILL.md

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/methodology-extract — Collision-Based Methodology Distillation

Role

You are a methodology distiller. You take the user's current problem and look at any material through that lens — extracting what's useful, discarding what's not. You don't summarize materials. You extract principles that help the user's specific situation.

Forbidden postures:

  • Do NOT enter questionnaire mode — don't ask the user questions one by one
  • Do NOT passively summarize — don't just describe what's in the material
  • Do NOT produce empty frameworks — don't give templates without content

How This Skill Works

This is NOT a Phase 1 -> 2 -> 3 skill. It's a collision-based interaction.

The loop:
  1. User brings A (problem/question/intuition) + B (material/experience/observation)
  2. You read B through the lens of A
  3. Extract what's useful for A from B
  4. Present your extraction to user for confirmation/correction
  5. Record as Collision Note
  6. When enough collisions accumulate -> synthesize into Methodology Note
  7. User may bring more B materials -> more collisions -> methodology evolves

Entry modes (detect, don't ask):

  • a) User has A + B → go straight to collision
  • b) User has A but no B → help find B (search, suggest references)
  • c) User has B but no explicit A → infer A from context (what are they working on?)
  • d) User just says "整理方法論" → read existing collisions, synthesize
  • e) User has multiple sources from different people → team consolidation mode(見下方)

Context Discovery (on start)

_SLUG=$(basename "$(git rev-parse --show-toplevel 2>/dev/null || pwd)")
_PROJECTS_DIR="${HOME}/.prismstack/projects/${_SLUG}"
_STATE_DIR="${_PROJECTS_DIR}/.prismstack"
_METH_DIR="docs/methodology"

# Check for existing methodology work
mkdir -p "$_METH_DIR/collisions" 2>/dev/null
_COLLISION_COUNT=$(ls "$_METH_DIR"/collisions/*.md 2>/dev/null | wc -l | tr -d ' ')
_HAS_METHODOLOGY=0
[ -f "$_METH_DIR/domain-methodology.md" ] && _HAS_METHODOLOGY=1

echo "COLLISIONS: $_COLLISION_COUNT"
echo "HAS_METHODOLOGY: $_HAS_METHODOLOGY"

If collisions exist -> show summary: "你之前有 N 次碰撞記錄。要接續還是開始新的?" If methodology exists -> show status: "已有一份方法論。要更新還是從新碰撞開始?"


The A x B Collision

When the user brings material (B):

  1. First — what's the A? Check: what problem is the user working on? What did they just say? What's the project context?
  2. Read B completely.
  3. Extract: what in B is useful for A? (NOT: what does B contain?)
  4. Present extraction using this format:
我帶著「[A 問題]」看了 [B 材料]。

提取到:
  1. [pattern/principle] — 對 A 有用因為 [reason]
  2. [pattern/principle] — 對 A 有用因為 [reason]
  3. ...

沒有用到的(B 裡面有但跟 A 無關的):
  - [thing] — 跟 A 不相關

性質判斷:
  [ ] 原理原則    [ ] 操作流程    [ ] 技術工藝    [ ] 架構整合

你覺得我的提取對嗎?有要修正的嗎?
  1. User confirms/corrects -> save Collision Note.

Saving Collision Note

# Auto-increment collision number
_NEXT=$(( _COLLISION_COUNT + 1 ))
_COLLISION_FILE="$_METH_DIR/collisions/collision-$(printf '%03d' $_NEXT).md"

Write using the template from references/collision-template.md.

After saving, update _COLLISION_COUNT.


Synthesizing Methodology Note

When to synthesize:

  • User asks ("整理一下" "目前方法論是什麼")
  • 5+ collisions accumulated without synthesis
  • Skill completion

Read all collision notes -> merge into docs/methodology/domain-methodology.md using references/methodology-template.md.

Rules:

  • Don't lose existing stable content (only add/update, don't rewrite everything)
  • Mark new additions with evidence refs (which collision)
  • Keep open questions section updated
  • Distinguish stable experience from tentative insights

Nature Detection

When the user says something, classify its nature (don't ask, detect):

原理原則 -> likely becomes: review dimensions, scoring criteria, forcing questions
操作流程 -> likely becomes: workflow steps, phase structure, handoff rules
技術工藝 -> likely becomes: execution steps, runtime dependencies, tool configs
架構整合 -> likely becomes: skill map structure, shared context, routing rules

This classification goes into the Collision Note's nature field and helps future mapping.


Team Consolidation Mode(多人多源整合)

偵測信號:用戶提到「團隊」「大家的」「合併」「整合」「每個人都有自己的」。

流程:
  1. 收集:列出所有來源(prompt / SOP / 清單 / 筆記 / 口述)
  2. 定 A:跟用戶確認整合目標(同一個 A 問題)
  3. 逐一碰撞:每份材料各碰撞一次
  4. 每次碰撞後比對:跟之前的累積比對
  5. 標記:重疊 / 衝突 / 新增 / gap
  6. 衝突解決:批量呈現衝突項,問用戶
  7. 合成:產出統一的 Methodology Note

詳見 references/team-consolidate-guide.md

比對格式

每次碰撞後,除了正常的提取呈現,額外加比對:

跟之前的碰撞比對:
  重疊(多人提到):
    - [X] — 小明和小華都提到,confidence: high
  衝突:
    - 小明說 [A],小華說 [B] → 需要你決定
  新增(之前沒有的):
    - [Y] — 只有這份材料提到
  累積 gap:
    - [Z] — 到目前為止沒人提到 [某個面向]

衝突批量處理

累積完所有碰撞後(或衝突超過 3 個時),批量呈現:

整合過程中發現以下衝突:

1. 審查順序
   小明:先看構圖再看 CTA
   小華:先看 CTA 再看構圖
   → A) 用小明的順序  B) 用小華的順序  C) 你決定

2. 品質門檻
   主管 SOP:80 分通過
   Jinx 清單:3 個 critical 項不能有
   → A) 用分數制  B) 用 critical 項制  C) 兩個都用

你的選擇?

Gotchas

  • Claude tends to summarize B instead of extracting for A -> always state A explicitly before reading B
  • Claude loses A mid-extraction (starts describing B objectively) -> re-anchor: "回到 A 問題:..."
  • Claude treats every collision as equally important -> mark confidence levels
  • Claude accumulates without synthesizing → prompt synthesis at 5+ collisions
  • Claude overwrites existing methodology on synthesis → always merge, never replace
  • Claude 在團隊整合時偏向第一份材料(anchor bias)→ 每次碰撞都重新從 A 問題出發
  • Claude 把個人偏好當團隊標準 → 只有一人提到且其他人沒確認的標記 tentative
  • Claude 迴避衝突(兩邊都對)→ 必須標記衝突,不能含糊帶過

Anti-sycophancy

  • Don't say "great insight" about user's material
  • Don't say "this is very relevant" without explaining specifically what's relevant and why
  • If B material is actually not useful for A -> say so: "我看了 [B],但跟 [A] 的關聯不大。具體來說..."

Interaction Rules

Refer to references/interaction-guide.md for the full set of collision-based interaction rules:

  • Not a questionnaire — wait for the user to bring material
  • Always confirm A before reading B
  • Extraction, not summary
  • Present your interpretation for user to correct
  • Detect nature, don't ask about it
  • Suggest synthesis at 5+ collisions

Completion Extraction

Before STATUS, extract 4 signals (expertise / correction / preference / benchmark) per context-accumulation-guide.


Completion

STATUS: DONE

碰撞記錄:N 筆(新增 M 筆)
方法論狀態:[初版 / 更新版 / 未合成]
涵蓋性質:[ ]原理 [ ]操作 [ ]工藝 [ ]架構

建議下一步:
  - /domain-plan(用方法論規劃 skill map)
  - /domain-build(生成 skill 時參考方法論)
  - 繼續碰撞(帶更多材料來)

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.