Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/gatelynch/llm-knowledge-base/braindumpgit clone --depth 1 https://github.com/gatelynch/llm-knowledge-baseWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00021 | $0.01067 |
| Opus 5 | $0.00010 | $0.00534 |
| Sonnet 5 | $0.00004 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00107 |
Grade A, and why
braindump scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
對話沉澱
把這次對話中討論過的想法沉澱成素材，存到 brainstorming/chat/。依照 CLAUDE.md 設定的語言回應。
流程
1. 確認範圍
先問使用者（等對方回覆才繼續）：
你想要怎麼記錄這次對話？
- 問答沉澱 — 記錄討論過程、結論、還沒想清楚的部分
- 文章草稿 — 根據對話生成文章架構，經你同意後才寫
- 兩者都要（分別存成不同檔案）
2. 決定檔名
格式：brainstorming/chat/YYYYMMDD {主題}.md
- 如果使用者有提供
$ARGUMENTS，用它當主題 - 如果沒有，從對話內容中提取主題
- 問答沉澱和文章草稿用不同檔名，例如：
20260404 重新打造第二大腦 問答沉澱.md20260404 重新打造第二大腦 文章草稿.md
3. 寫問答沉澱
如果使用者選了 1 或 3，按以下格式寫：
---
question: "這次對話的核心問題（一句話）"
asked_at: YYYY-MM-DD
sources: [[[相關的 vault 檔案]]]
---
內容結構
- TL;DR：2-3 句話總結這次對話最重要的收穫
- 結論：對話中形成的洞見，分主題列出。每條要有具體內容，不是空泛的摘要
- 證據：
- 對話中挖出的反例與張力
- vault 中的佐證（附
[[連結]]） - 使用者自己舉的具體例子
- 不確定性：還沒想清楚的問題、懸著的問題、有矛盾但還沒解決的地方
重要原則
- 區分「使用者自己說的」和「AI 提出的」——使用者的原話和立場要忠實保留
- 使用者說「還沒想清楚」的地方，就記「還沒想清楚」，不要幫他補答案
- sources 只列對話中實際引用或搜尋過的 vault 檔案
4. 寫文章草稿
如果使用者選了 2 或 3：
4a. 先提出文章架構
根據對話內容，生成一個 3-5 段的文章架構，每段包含：
- 段落標題
- 1-2 句話說明這段要寫什麼
架構要遵循 CLAUDE.md 中定義的寫作風格。預設原則：
- 從真實故事出發 → 反轉 → 帶著疑惑反思 → 留下沒有答案的問題
- 不用「總結來說」收尾
- 問完問題不給答案
把架構給使用者看，等使用者同意或修改後才繼續寫。
4b. 寫草稿
使用者同意架構後，寫成完整文章草稿，存到 brainstorming/chat/。
草稿原則：
- 用對話中使用者自己的語言和例子，不要另外發明
- 使用者沒說過的故事不要編
- 對話中懸著的問題，在文章中也讓它懸著
- 這是草稿，放在 brainstorming/ 而非 artifacts/——使用者自己決定什麼時候搬到 artifacts/
原則
- 先問再做：不要假設使用者要哪種格式
- 文章架構一定要先給使用者看過：沒有同意不動手寫
- 不主動搬到 artifacts/：brainstorming/chat/ 是 AI 的，artifacts/ 是使用者自己的
- 素材不夠就說清楚：如果對話內容太短或太散，誠實說，不要硬湊
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 97 lines · 21 tokens per session scan A 38d0eef3f351
braindump is a command published in the GitHub repository gatelynch/llm-knowledge-base (327 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,067 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.