task-done

task-done is a skill for Claude Code, Codex from Stanshy/AgentHub. It costs 24 tokens per session (1,076 once invoked), scanned A, original, MIT.

A task-completion procedure that submits a development task for L1 review, where L1 is the first-level review stage. It checks the task's acceptance criteria, records the completion time, updates its status, and adds the result to section 10 of the development plan.

In plain words
What is it for?
Use it when a task is complete and should move to in_review, including checking off confirmed acceptance items and adding notes for anything that cannot be verified.
Why use it?
It prevents unfinished or unverified tasks from being submitted as ready for review. It also keeps the task record and development plan consistent.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/stanshy/agenthub/task-done
Any agent
npx skills add Stanshy/AgentHub --skill task-done
Clone the repo
git clone --depth 1 https://github.com/Stanshy/AgentHub

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for task-done

README.md
[![agentmods](https://agentmods.dev/badge/skills/stanshy/agenthub/task-done.svg)](https://agentmods.dev/skills/stanshy/agenthub/task-done)
Your own site
<a href="https://agentmods.dev/skills/stanshy/agenthub/task-done"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/task-done.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,076 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.01076
Opus 5 $0.00012 $0.00538
Sonnet 5 $0.00005 $0.00215
Haiku 4.5 $0.00002 $0.00108

Measured 4d ago against content hash cf0f7c8f27a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

task-done 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 4d 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.

.knowledge/company/skill-templates/task-done/SKILL.md · 88 lines

What it actually says

任務完成提交

更新任務狀態為 in_review(待 L1 審查),並在開發計畫書第 10 節記錄。

使用方式

/task-done <task-id> [備註]

參數

  • $0: 任務 ID(如 T1
  • $ARGUMENTS: 完整參數(含備註)

格式規範(系統解析依賴,務必遵守)

.tasks/ 狀態欄位(第 2 欄 | 狀態 | xxx |

必須使用以下英文值:

狀態值 說明
in_review 待 L1 審查

dev-plan 第 10 節「結果」欄位(第 3 欄)

結果值 對應系統狀態 說明
🔍 待審查 in_review 已提交,待 L1 Review
🔧 需修正 in_review 需返工

系統解析器 normalizeStatus() 依賴 完成/✅/修正/🔧 等關鍵字判斷。

日期欄位(第 2 欄)

格式:YYYY-MM-DD

執行步驟

  1. 找到對應的任務檔案(支援 Sprint 子目錄): 使用 Glob tool 搜尋 .tasks/**/$0-*.md,若無結果再搜尋 .tasks/**/$0.md。 取得檔案路徑後用 Read tool 讀取內容。

任務檔案可能在 .tasks/sprint-{N}/T1-xxx.md,不再只在 .tasks/ 根目錄。

  1. 驗收標準確認(必要)

    • 讀取任務檔案,找到 ## 驗收標準 區塊
    • 逐項檢查每個 - [ ] 項目是否已完成
    • 將所有已完成的項目打勾:- [ ]- [x]
    • 如果有項目無法確認完成,必須在備註中說明,不可跳過
  2. 取得真實時間(必要,不可跳過): !node -e "console.log(new Date().toISOString())"

    ⚠️ 禁止自行編造時間。Agent 不知道真實時間,必須透過上述指令取得。將輸出存為變數 $NOW 供後續步驟使用。

  3. 更新找到的任務檔案:

    • | 狀態 | ... | 改為 | 狀態 | in_review |
    • | 完工時間 | ... | 改為 | 完工時間 | $NOW |
    • 完工時間 已有非 的值,不覆蓋(代表被退回後重新提交,保留首次完工時間)
    • 若找不到 | 完工時間 | 欄位,在 | 建立時間 | 行之後插入 | 完工時間 | $NOW |
    • ## 事件紀錄 區塊底部 append:
    ### $NOW — 狀態變更 → in_review
    {備註}
    
  4. Git Commit

    • 讀取任務檔的 | 並行組 | 欄位
    • 若循序任務(並行組 = —):確認當前在 sprint-{N} branch
    • 若並行任務:確認當前在 task/s{N}-$0-* branch
    • 判斷 commit type(feat / fix / refactor / docs / test / chore)
    • 執行:
      git add -A
      git commit -m "{type}: {任務標題} ($0)"
      
  5. 找到當前 dev-plan: 使用 Glob tool 搜尋 proposal/sprint*-dev-plan.md,取最新一份用 Read tool 讀取。

  6. 在 dev-plan 第 10 節「任務完成紀錄」表格,找到對應任務行並更新:

| $0 | {YYYY-MM-DD} | 🔍 待審查 | {備註} |
Changes

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.

  1. 4d ago First seen · 88 lines · 24 tokens per session scan A cf0f7c8f27a4

Subscribe to this mod's changes

task-done is a skill published in the GitHub repository Stanshy/AgentHub (200 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 1,076 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.

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