一键导入
compute
Use to compute summary statistics (count/sum/mean/min/max) from a readings artifact, preserving the upstream source trace. Single tool. Reusable standalone.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Use to compute summary statistics (count/sum/mean/min/max) from a readings artifact, preserving the upstream source trace. Single tool. Reusable standalone.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when deciding whether to write a piece of code, add a dependency, or introduce an abstraction / module / config — the "should I build this at all?" filter, applied before building. | 要決定「要不要寫這段 code/引這個依賴/加這層抽象或模組」時使用——「到底該不該做」的過濾網,動手之前先走一遍。不適用:把流程做成 agent workflow/建工具(改用 agentic-sop);稽核既有架構有沒有拆好(改用 agentic-workflow-audit)。
demo good plugin
Use when creating, scaffolding, or linting a Claude Code plugin — generate a grammar-conformant plugin skeleton, or validate a plugin / whole marketplace against house invariants (manifest, frontmatter, stdlib-only, hook protocol, test harness). | 要新建 / scaffold 一個 Claude Code plugin,或 lint 既有 plugin / 整個 marketplace 是否符合房規時使用。
Use when checking a record / dataset / GMP document for ALCOA+ data integrity — attribution, contemporaneity (backdating), completeness, accuracy (recompute / in-spec), consistency — before a human approves. DEGRADED mode lints any CSV/JSON record against a declared .alcoa.json contract; FULL mode snaps onto an agentic-sop-kit run dir. | 要檢查紀錄/資料/GMP 文件的資料完整性(ALCOA+:可歸屬、同步性/防 backdating、完整、正確、一致)時使用。輸出為 DRAFT,人擁有最終判定;確定性檢查只覆蓋可機械驗證的部分,其餘列為人判斷清單,絕不臆造。
Use when asked to get a second opinion on a finished DRAFT, fact-check or double-check a report's claims against its evidence, sanity-check before sign-off, or red-team an output for fabrication / overreach / invented IDs — even without the word "honesty". Works on an agentic-sop-kit run dir (FULL, uses the run's trace) or any plain document (DEGRADED, you supply the inputs). | 要對一份已完成的 DRAFT 取得「第二意見」、在核准前查核報告主張是否有輸入佐證、抓臆造/灌水/過度宣稱/捏造編號時使用;吃 agentic-sop-kit 的 run 目錄(FULL,用 trace)或任何純文件(DEGRADED,需自備輸入)。不適用:稽核 agent 架構有沒有拆好/是不是 mega-agent(改用 agentic-workflow-audit);審查原始碼品質/bug/資安(改用 /code-review)。本 skill 只查「這次產出的主張 vs. 證據」誠實度,只產 DRAFT,核准永遠人擁有。
Use when turning a human SOP or manual process into an agentic workflow, building or adding an agent tool, or starting a new agent-workflow project — even if the user never says 'SOP' or 'methodology'. | 要把人工流程/SOP 自動化、建立或新增 agent 工具、或開一個新的 agent 工作流專案時使用;只要意圖是把流程工程化成自動代理就觸發。不適用:稽核既有工作流是否退化成 mega agent(改用 agentic-workflow-audit)。
| name | compute |
| description | Use to compute summary statistics (count/sum/mean/min/max) from a readings artifact, preserving the upstream source trace. Single tool. Reusable standalone. |
SOP 流程的第 2 步。讀上游 readings、算統計、透傳來源追溯。
python3(標準庫 statistics)。本 skill 只此一個工具。python >= 3.8--in <readings artifact.json>--out <stats artifact.json>readings@1(讀 data.readings[].value)。{"schema":"stats@1","produced_by":"compute","data":{"stats":{count,sum,mean,min,max}},"trace":[...透傳...]}data.stats 與 trace。python3 skills/compute/tool.py --in <out/a.json> --out <out/b.json>
skills/compute/ + lib/kit.py 可單獨抽出;只要上游給 readings@1 artifact 即可運作。