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 Stanshy/AgentHub --skill task-donegit clone --depth 1 https://github.com/Stanshy/AgentHubWrote 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/stanshy/agenthub/task-done)<a href="https://agentmods.dev/skills/stanshy/agenthub/task-done"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/task-done/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/stanshy/agenthub/task-done"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/task-done.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 | $0.00024 | $0.01076 |
| Opus 5.5 | $0.00010 | $0.00430 |
| Sonnet 5.5 | $0.00005 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00108 |
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 1mo 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
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
- 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。
-
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
- 讀取任務檔案,找到
-
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。 -
更新找到的任務檔案:
- 將
| 狀態 | ... |改為| 狀態 | in_review | - 將
| 完工時間 | ... |改為| 完工時間 | $NOW | - 若
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 | - 在
## 事件紀錄區塊底部 append:
### $NOW — 狀態變更 → in_review {備註} - 將
-
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)"
- 讀取任務檔的
-
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。 -
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} |
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.
- 1mo ago First seen · 88 lines · 24 tokens per session scan A cf0f7c8f27a4
task-done is a skill published in the GitHub repository Stanshy/AgentHub (204 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 1,076 once invoked, about $0.0001 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 2026-08-30.
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