EngramGraph: Skill for Claude Code

Brainstorm Assistant | 腦力激盪助手

Language: English | 繁體中文

Structured ideation before specification writing. Transform vague ideas into actionable feature proposals through guided brainstorming — grounded in 2024–2026 research on AI-assisted ideation.

在撰寫規格前進行結構化發想。以 2024–2026 年 AI 輔助發想研究為基礎，透過引導式腦力激盪，將模糊構想轉化為可執行的功能提案。

Implements: XSPEC-296 Brainstorm Quality Standard (BQS v1) — brainstorm v4, layered on XSPEC-247 brainstorm v3 (Multi-Persona Ensemble + Multi-Critic Convergence).

What changed in v3 | v3 的核心改動: Divergence is no longer a single AI voice racing to a count — it is a persona ensemble (each role reasons via chain-of-thought, in isolation) crossed with diversity lenses. Convergence is no longer one AI scorer plus one devil's-advocate — it is a multi-critic panel plus a hard-role rebuttal (Devil's Advocate + Steelman). This directly targets the strongest finding in the literature: multiple personas beat a single pass, and a single LLM critic is weak and prone to sycophancy.

v3 把發散從「單一 AI 衝數量」改為persona 集成（每個角色以思維鏈獨立推理）× 多樣性透鏡；把收斂從「單一 AI 評分 + 單一反駁」改為多評審面板 + 硬角色反駁（Devil's Advocate + Steelman）。直接對應文獻最強結論：多 persona 勝過單一 pass，單一 LLM 評審既弱又易諂媚。

What changed in v4 | v4 的核心改動: v3 supplied strong mechanisms but no decidable pass/fail quality gate. v4 layers a time-sequenced quality contract on top — the Brainstorm Quality Standard (BQS v1) — without removing any v3 behaviour. BQS is a four-layer × timeline structure: Layer 0 declares explore/exploit intent; Layer 1 (process, leading, visible during divergence) runs dimensions D1–D4; Layer 2 (product, leading, applied to the Recommended Set only after convergence — ideas with Agg. Score ≥ 3.5, uncapped) runs D5–D8 plus a Seeds column and a contested zone; Layer 3 is an ungoverned Judgment Override. First principle: decisions use leading signals; calibration uses lagging signals — these are ordered in time, not a right/wrong trade-off. The hard sequence gate forbids D5–D8 from being revealed or scored during divergence. See "BQS v1 — Quality Contract" below.

v4 的核心改動： v3 提供了強健的機制，卻沒有可判定 pass/fail 的品質閘。v4 在其上疊加一道時序化品質契約——腦力激盪品質標準（BQS v1）——且不移除任何 v3 行為。BQS 是四層 × 時間軸結構：第 0 層宣告 explore/exploit 意圖；第 1 層（過程、leading、發散期全程可見）跑維度 D1–D4；第 2 層（產物、leading、收斂後僅施於推薦集，即 Agg. Score ≥ 3.5、不限筆數的想法）跑 D5–D8 加 Seeds 欄與爭議區；第 3 層是不受治理的 Judgment Override。第一原理：決策用 leading 訊號、校準用 lagging 訊號——兩者是時間前後，而非對錯取捨。 硬序列閘禁止 D5–D8 在發散期被揭示或評分。詳見下方「BQS v1 — 品質契約」。

What changed in v4.2 (XSPEC-388) | v4.2 的核心改動: D4 pinned where the judge sits and said nothing about whether it can think. An independent context running a literal-following model satisfies the old wording verbatim and rubber-stamps its way through D5–D8 — indistinguishable on paper from a review where someone actually objected. v4.2 gives D4 a second axis: the review must also declare its required model level (see the terminology note below). The CONVERGE briefs are re-shaped as goal + constraints — D5–D8 are criteria the judgment must satisfy, not steps to execute in order; the fixed sentence patterns and per-criterion scoring guides are kept as reference formats. The divergence side cites core/model-selection.md (Standard or higher) instead of adding a rule of its own. No v3 mechanism is removed.

v4.2 的核心改動（XSPEC-388）： D4 原本只釘住判官坐在哪裡，一個字都沒說它得想得動。一個獨立 context 跑字面遵循型模型會逐字滿足舊條文，然後照 D5–D8 逐條打勾放行——與一場真的有人反對過的評審在報告上無從分辨。v4.2 給 D4 加上第二個軸：評審還必須宣告其模型層級要求（見下方術語說明）。CONVERGE 的提示改為目標＋約束形狀——D5–D8 是判斷必須滿足的判準，不是按順序執行的步驟；既有固定句型與逐準則分數指南保留為參考格式。發散側引用 core/model-selection.md（Standard 或更高）而不另立規則。不移除任何 v3 機制。

Terminology — "model level", never "tier" | 術語——「模型層級」，不用「tier」: inside this skill, tier is already taken twice — the BQS tiering table (which dimensions apply) and the Enhanced Tier. The model-capability axis defined in core/model-selection.md (called model tier there) is therefore always written model level（模型層級） in this skill. Model levels are that standard's vendor-neutral labels; this skill never names a concrete vendor model (see D4).

在本 skill 內，tier 已被佔用兩次——BQS 分級表（套用哪些維度）與 Enhanced Tier。core/model-selection.md 定義的模型能力軸（該標準稱 model tier）在本 skill 一律寫作模型層級（model level）。模型層級是該標準的廠商中立標籤；本 skill 絕不指名具體廠商模型（見 D4）。