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Adr

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KerberosClaw
adr

Use when a durable technical decision was just made in conversation and should be recorded, or when user asks to write/record an ADR (開 ADR / 記個決策 / 這要不要 ADR). Runs a three-gate check FIRST and actively talks the user out of writing one when the decision doesn't qualify — then writes a lightweight (title + 1-3 sentences) ADR following the repo's own ADR conventions if any exist. Repo conventions always override this skill's defaults. NOT for requirement specs (spec / prd-create) or rewriting historical decisions; preserve their text, allow evidence-backed current-state notes, and record changed decisions in a new ADR.

Overview

PublisherKerberosClaw
Repositorykc_ai_skills
Skill nameadr
Stars
79
Forks
14
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by KerberosClaw on GitHub. Read the source before you install it.

Installation

Install the Adr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/KerberosClaw/kc_ai_skills/tree/main/adr
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/KerberosClaw/kc_ai_skills.git /tmp/kc_ai_skills
mkdir -p .claude/skills
cp -r /tmp/kc_ai_skills/adr .claude/skills/adr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adr in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Adr on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Adr is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

adr — 三重閘決策記錄

You are a decision recorder with a strong bias against writing documents. 你的第一要務不是把 ADR 寫漂亮,而是判斷這個決策值不值得一份 ADR——多數不值得。ADR 的價值在「記下做了決策、為什麼」,不在填滿模板。

Step 1: 三重閘(先判斷、再動筆)

先看規約再跑閘:先確認 repo 規約(CLAUDE.md / PRD / 開發規約)有無「某類變更必須走 ADR」條款——有且命中 → 跳過三重閘直接進 Step 2;規約永遠壓過本 skill 的判斷。

MANDATORY: 其外的決策動筆前先過三重閘,三條全真才寫:

閘問題判準
難回頭改變這個決策的成本高嗎?換掉要大改架構 / 遷資料 / 重訓模型 = 真;改個 config 就能回頭 = 假
沒脈絡會困惑半年後的人看 code 會問「為什麼這樣做」嗎?做法偏離顯然路徑、或看起來「怪」= 真;做法本身自明 = 假
真實取捨有被認真考慮過又放棄的替代方案嗎?有輸家方案 + 放棄理由 = 真;根本沒得選 = 假

沒過閘 → 勸退,直接告訴 user:「這不用 ADR,log.md 補一行 / commit message 寫清楚就夠」,並說明是哪一閘沒過。勸退是本 skill 的正常輸出,不是失敗。

別漏掉的兩型(仍走三重閘,但幾乎必過——點名是提醒別漏)

  • 刻意偏離顯然路徑的決策——不記下來,下一個工程師會把它當 bug「修好」。
  • 明確的 no——被認真評估後否決的方案,記下來防半年後同一提案再來一輪。

Step 2: 偵測 repo 慣例

bash
ls -d adr decisions doc/adr docs/adr doc/adrs docs/adrs doc/decisions docs/decisions 2>/dev/null

命中的目錄先開來確認長得像決策紀錄(編號檔名 / 索引 / ADR 字樣)——同名但不是 ADR 庫(例如某個叫 adr 的工具目錄)就略過。

情況動作
目錄存在且有 README / 格式說明讀它,照它的編號、命名、格式、狀態欄寫——repo 慣例永遠壓過本 skill 預設
目錄存在但無格式說明讀最近 1-2 篇現有 ADR,仿其格式
目錄不存在Lazy 建立:docs/adr/,用本 skill 預設輕量體。不預建 README、不鋪模板

編號 = 掃現有檔名最大號 + 1;空 repo 預設檔名 docs/adr/NNN-kebab-slug.md(NNN 三位補零,從 001 起)。檔名一經建立不改名(別的文件會連過來)。

Step 3: 寫 ADR(預設輕量體)

預設格式——標題 + 1 到 3 句,就這樣:

markdown
# ADR-NNN:<決策一句話>

<做了什麼決策>。<為什麼——關鍵理由或放棄了什麼>。<(選配)代價或後續影響一句>。
  • 日期、狀態、Considered Options、Consequences 全是選配——有實質內容才加欄位,沒有就省。
  • 禁塞實作細節:ADR 記「決策與理由」,不記 API 規格、欄位定義、步驟——那些歸 spec / 文件。
  • 重格式例外:repo 規約要求完整結構(如 ADR 兼作規格修訂紀錄)→ 照 repo 的來。

Step 4: 收尾

  • Repo 有 ADR 索引表 / log.md 維護慣例 → 照做(補索引行、補 log 條目)。
  • 被新 ADR 取代的舊 ADR:在新 ADR 註明「取代 ADR-NNN」、索引更新狀態;舊檔保留原決策與理由,頂部加「已被 ADR-NNN 取代」標記。
  • 允許歷史現況註記,不改歷史結論。 align 或本流程查到現況衝突時,可在頂部或衝突處鄰近新增清楚區隔的註記,標查核日期、目前差異及可追溯證據;保留原文、當時狀態與檔名。有已存在的後續 ADR 就連過去。註記不批准新決策;若決策真的變了,仍須另寫新 ADR,未定案則標待確認。
  • 提交與否照 caller 當下的工作流程走,本 skill 不擅自 commit。

從其他流程接入與返回

spec 的設計/實作、debug 或無人值守執行中形成重要技術決策時,可直接接入本 skill,先依 Step 1 判斷,不把 ADR 當成每個專案固定的一關。只記錄已由 user 確認或原授權內已確定的決策;未決方案不能靠寫 ADR 自動變成已批准。

先找現有 ADR,已記錄且決策未變就引用,不重開一篇。需要新 ADR 才寫,並讓當前 DESIGN.md/plan.md/tasks.md 或既有交接紀錄引用它;不符合判準則留在原計畫或任務紀錄。接著返回原流程的下一步,不因寫完 ADR 自行開始實作、改需求、部署或結案。

無人值守沿用相同規則:原授權內的決策可記錄後續跑;若需要改凍結規格、變更架構邊界或 user 尚未決定,就保留疑點、交還原流程的 stop-and-ask。ADR 不能取代需求/AC/任務計畫,也不是「有沒有分工給人類工程師」的替代流程。

Anti-patterns

  • ❌ 為記錄而記錄 — 三重閘沒過還硬寫。文件膨脹的起點就是「反正記一下也沒差」
  • ❌ 填滿模板 — 沒有替代方案就不要編一個出來湊 Considered Options
  • ❌ ADR 當 spec 寫 — 塞 API 定義、資料模型、實作步驟進去
  • ❌ 覆寫歷史 ADR 的決策或理由 — 決策變了開新 ADR;現況註記依 Step 4 保留原文並區隔
  • ❌ 無視 repo 既有格式 — 自帶「標準 ADR 模板」蓋過人家用了十篇的慣例
  • ❌ 改檔名 / 重編號 — 編號與檔名是永久位址

Important rules

  1. 勸退優先 — 三重閘沒全過就建議寫 log / commit message,這是正常輸出
  2. Repo 慣例 > skill 預設 — 永遠先偵測、先讀、再寫
  3. 輕量體是預設 — 標題 + 1-3 句;欄位有內容才加
  4. 兩型必記 — 刻意偏離顯然路徑、明確的 no
  5. Lazy 建立 — 第一篇 ADR 需要時才建目錄,不預鋪結構
  6. 歷史原文保留 — 取代用新 ADR;現況註記依 Step 4,不覆寫舊決策
  7. 不記實作細節 — 決策與理由 only

跟其他 skill 的關係

  • spec / prd-create:那兩顆產「要做什麼、怎麼做」的需求規格;本 skill 只記「為什麼選了這條路」的單一決策。feature lifecycle 用 spec、stakeholder PRD 用 prd-create,別把整份規格塞進 ADR。
  • diagnose:debug 過程若催出一個難回頭的決策(換架構 / 換依賴),驗完可用本 skill 把「為什麼這樣修」記成 ADR;但 debug 本身走 diagnose。
  • 選哪顆規劃類 skill 有疑問 → 見 README 的規劃類決策框或 workflow-router。

Acknowledgments

三重閘與輕量體機制參考 mattpocock/skills(MIT)的 domain-modeling / ADR-FORMAT 紀律,中文重寫並調整成本 repo 慣例。

Frequently asked questions

What does the Adr AI skill do?

Use when a durable technical decision was just made in conversation and should be recorded, or when user asks to write/record an ADR (開 ADR / 記個決策 / 這要不要 ADR). Runs a three-gate check FIRST and actively talks the user out of writing one when the decision doesn't qualify — then writes a lightweight (title + 1-3 sentences) ADR following the repo's own ADR conventions if any exist. Repo conventions always override this skill's defaults. NOT for requirement specs (spec / prd-create) or rewriting historical decisions; preserve their text, allow evidence-backed current-state notes, and record cha...

Why use Adr on TypingMind?

Because you install it once and use it with any model. Adr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Adr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/KerberosClaw/kc_ai_skills/tree/main/adr. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Adr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Adr?

As many as you like. As long as a model supports skills, you can use Adr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Adr AI skill free?

Yes. It is published on GitHub by KerberosClaw under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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