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 skills add curtischoutw/claude-institution --skill lessongit clone --depth 1 https://github.com/curtischoutw/claude-institutionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/curtischoutw/claude-institution/lesson)<a href="https://agentmods.dev/skills/curtischoutw/claude-institution/lesson"><img src="https://agentmods.dev/badge/skills/curtischoutw/claude-institution/lesson/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curtischoutw/claude-institution/lesson"><img src="https://agentmods.dev/badge/skills/curtischoutw/claude-institution/lesson.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00111 | $0.00783 |
| Opus 5 | $0.00056 | $0.00392 |
| Sonnet 5 | $0.00022 | $0.00157 |
| Haiku 4.5 | $0.00011 | $0.00078 |
Grade A, and why
lesson 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 9d 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
lesson：把教訓寫成規則並升級
目的：讓每次糾正只發生一次。
0. 先分流：這是事實/偏好，還是規則？
- 單純事實／偏好／build 指令（「這個專案用 pnpm」「使用者偏好簡短回報」） → 交給內建 auto memory（預設開啟、自動記錄，無人工步驟），不進本流程。
- 需要變成「以後都要遵守」的規則 → 走下面 A／B 節。
A. 記錄一條新 lesson
先查重：在 tasks/lessons.md 搜尋關鍵字，已有同類條目 → 不新增，改走「B. 升級」。
用固定格式追加（檔案不存在才建立）：
## [YYYY-MM-DD] <一行標題：動詞開頭>
- 觸發情境：<具體到下一個 session 能比對，含檔名/指令/使用者原話>
- 錯誤行為：<我實際做了什麼>
- 正確行為：<應該做什麼，可執行的一步步>
- 判準：<一句 if-then，讓弱模型能機械式套用>
- 狀態：first-hit
判準欄位不可空白：寫不出 if-then 表示還沒想清楚，再想。太抽象等於沒寫—— 壞例「要更小心測試」對照好例「改任何公開函式簽名前先 grep 所有呼叫端」，差別在 後者具體到下一個 session 能直接比對情境，不是換個說法重複同一句空話。
B. 升級（同一 lesson 第 2 次被觸發時）
- 把該條目的
狀態：first-hit改為狀態：promoted-to:<位置>。 - 依「制度分層」選升級目的地：
- 規則可用程式判定（如「禁止 commit 含 console.log」）→ 用 /update-config 做成 hook。最優先。
- 1–2 行寫得完、每次都適用 → 加進 CLAUDE.md 的「硬規則」，加一條前先看能否刪一條。
- 多步驟程序 → 寫成 skill，CLAUDE.md 留一行觸發指引。
- lessons.md 的原條目保留（作為升級紀錄），不刪除。
鐵則
- 糾正發生的當下就記，不要等任務結束（會忘）。
- 一條 lesson 只記一個模式；混多個就拆開。
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.
- 9d ago First seen · 49 lines · 111 tokens per session scan A 2afde190f9c6
lesson is a skill published in the GitHub repository curtischoutw/claude-institution (5 stars, last pushed 9d ago), licensed MIT. It adds 111 tokens to every session and 783 once invoked, about $0.0006 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 2026-08-31.
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