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 KerberosClaw/kc_ai_skills --skill aligngit clone --depth 1 https://github.com/KerberosClaw/kc_ai_skillsWrote 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/kerberosclaw/kc_ai_skills/align)<a href="https://agentmods.dev/skills/kerberosclaw/kc_ai_skills/align"><img src="https://agentmods.dev/badge/skills/kerberosclaw/kc_ai_skills/align/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/kerberosclaw/kc_ai_skills/align"><img src="https://agentmods.dev/badge/skills/kerberosclaw/kc_ai_skills/align.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 | $0.00107 | $0.03004 |
| Opus 5.5 | $0.00043 | $0.01202 |
| Sonnet 5.5 | $0.00021 | $0.00601 |
| Haiku 4.5 | $0.00011 | $0.00300 |
Grade A, and why
align 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
align — 讓文件跟上實作
以目前實作與可查證的執行紀錄補齊既有文件，適用於 hotfix 後文件沒跟上，或無人值守任務跑完 QA 後的全 repo 對齊。呼叫本 skill 即授權修改目標 repo 的文件；user 明確要求唯讀時，只回報落差。
使用方式
/align
/align /path/to/repo
這個 repo 跑一輪文件對齊
/align 只對齊這次刪掉 legacy/ 目錄的影響
/align 全庫重掃
無人值守執行 align，目標 /path/to/repo
有兩種入口：在 repo 內用 /align 或「文件對齊」等關鍵字直接呼叫；無人值守任務跑完 QA 後，也可以接著跑一輪，再由原任務收尾回報完成。手動呼叫不要求先跑 QA；align 不代替 QA，不處理開票、結案或歸檔，也不建立排程。
spec／goal-engineer 的完整無人值守 build 主線為 實作與 AC／測試驗證 → doc-qa:qa 適用性與必要實跑 → align → 收尾回報。接收前一階段的 QA 報告、版本與證據；已查證無 UI 時承接不適用結論與原 AC／適用驗證，不把它改成 UI PASS。若有 UI 卻未實跑或仍有缺陷，可處理已確定的文件落差，但保留缺口，不改需求或 QA 結果替缺陷背書。align 完成後回到原執行 agent 統一回報。
對齊範圍
| 範圍 | 適合的情況 | 做法 |
|---|---|---|
| 觸發範圍 | 起因是一件明確的改動：某個 hotfix、刪除或搬走的檔案／目錄、改名的介面／參數／指令、某段 commit 區間 | 從觸發事件列出搜尋鍵，在整個 repo 找引用到它的文件，只查證、修訂這些；範圍外看到的落差只記錄 |
| 全庫重掃 | 沒有單一起因、很久沒對齊、交接或發布前、無人值守主線 QA 後 | 照下方流程盤點整個 repo |
怎麼決定：
- 手動呼叫：第 1 步完成後、開始盤點前，先問 user 要用哪一種。只問這一題，並附上建議：辨認得出具體觸發事件就建議觸發範圍，且把你辨認出的事件寫進選項讓 user 確認；辨認不出就建議全庫重掃。user 的請求已講明範圍（例如「只對齊這次刪除的影響」「全庫重掃」）就不再問。
- 無人值守：不問。照 dispatch 指定的範圍；沒指定就全庫重掃，這是 spec／goal-engineer 主線的預設。
- 觸發範圍跑到一半，發現同類落差明顯散到觸發事件之外：手動時回報並問要不要轉全庫重掃；無人值守時記成範圍外發現。都不自行擴大修訂範圍。
執行流程
-
確定目標、規則與範圍。 使用明確指定的 repo，否則以目前 Git 根目錄為準；無法定位時才問。讀適用的
AGENTS.md／CLAUDE.md，wiki 型 repo 先讀SCHEMA.md。記錄 HEAD 與既有工作區變更，保留他人的修改，不自動 stash、reset、切換版本或更新 checkout。接著照「對齊範圍」決定這次用哪一種。 -
盤點。 先讀 references/criteria.md 中對應範圍的覆蓋判準。
- 全庫重掃：列出維護中的說明、操作手冊、架構／介面文件、規格、歷史記錄與入口索引，對照程式、設定、測試及已有 QA 證據。Git log／diff 用來追原因，不能只看最近一次變更。跳過
.git、依賴、快取與產生檔等非維護來源；大 repo 分批閱讀並保留覆蓋清單，未讀完不得說全庫已對齊。 - 觸發範圍：把觸發事件寫成一句話，列出搜尋鍵，用它們掃整個 repo 的維護文件，命中的段落逐條讀完並核對目標的現況。命中清單就是這次的覆蓋範圍。
- 全庫重掃：列出維護中的說明、操作手冊、架構／介面文件、規格、歷史記錄與入口索引，對照程式、設定、測試及已有 QA 證據。Git log／diff 用來追原因，不能只看最近一次變更。跳過
-
查證差異。 修改前先讀 references/criteria.md，依其中的證據與修訂判準逐項核對。沿文件引用追到相關 repo 的實作、介面、呼叫方或部署紀錄；對同一 repo／引用去重，已走過的循環不重追。外部 repo 的用途是查清本 repo 的敘述，不擴成無關 repo 的全面掃描。
-
直接修訂目標 repo 的文件。 更新現況敘述、使用方式、參數、流程與交叉連結；同步受影響的既有索引與翻譯，遵循 repo 慣例，不另起一套文件架構。文件本身標明是歷史紀錄、已結案或 ADR 的才算歷史記錄，保留原文並在有衝突時加註目前差異與依據；其他一律當現況文件直接修。無法確認的項目保留並回報，先完成其他可確定部分。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 98 lines · 107 tokens per session scan A 2e3c9a42e0df
align is a skill published in the GitHub repository KerberosClaw/kc_ai_skills (79 stars, last pushed 2d ago), licensed MIT. It adds 107 tokens to every session and 3,004 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-16.
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