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 agentmods add skills/lee-w/maigo/work-boardnpx skills add Lee-W/maigo --skill work-boardgit clone --depth 1 https://github.com/Lee-W/maigoWrote 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/lee-w/maigo/work-board)<a href="https://agentmods.dev/skills/lee-w/maigo/work-board"><img src="https://agentmods.dev/badge/skills/lee-w/maigo/work-board.svg" alt="Measured on agentmods" 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 | $0.00112 | $0.09467 |
| Opus 5 | $0.00056 | $0.04734 |
| Sonnet 5 | $0.00022 | $0.01893 |
| Haiku 4.5 | $0.00011 | $0.00947 |
Grade A, and why
work-board 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 5d 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 — 426 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work Board
Owner Agent: orchestrator（直跑，不 delegate 五人）
Consumers: /maigo:board（讀寫全套）、
/maigo:review、
/maigo:triage-issue、
/maigo:take-issue、
/maigo:address-comments、
/maigo:describe-pr（各自的收尾回寫段）
Why this skill exists
/maigo:review 的 .maigo/review-board.md 只涵蓋「reviewer 視角」。實際工作面是三種混在一起的球：
要 triage / 接的 issue、自己開的 PR、在審別人的 PR。Work Board 把它們併成一份，
核心機制沿用 review board 最有價值的部分：board 的存在意義不是收藏分類，
而是回答「現在該我動哪些」。
1. .maigo/board.md 格式規格
Sections（固定順序，三個 section 即 treesitter fold 邊界）
# Work Board — Lee-W/maigo
> 最後刷新：2026-08-18 14:30 ｜ 🎯 3 ｜ ⏳ 2 ｜ ✅ 1 ｜ 🧠 待學習盤點 1
## 🎯 下一件（3）
1. [ ] 🔀 CHANGES_REQUESTED i/9201.md — Redesign Work Board reading view
2. [x] 👀 ↩︎ 回你的球 i/9301.md — Avoid duplicate GitHub requests
3. [ ] 🐛 待 triage 💤 i/9101.md — CLI 在空設定檔時會 crash
## ⏳ 等別人（2）
- [ ] 🔀 等 review i/9202.md — Document plugin installation flow
- [ ] 🐛 NEEDS_INFO（已請補作業系統與完整 log） i/9103.md — Hook occasionally exits without output
## ✅ 最近結案（1）
- [x] 👀 APPROVE（merged 07-12） 🧠 i/9303.md — Add structured review verdicts
i/9201.md 對應的細節檔（相對 .maigo/）：
# 🔀 CHANGES_REQUESTED — Redesign Work Board reading view
- 連結：https://github.com/Lee-W/maigo/pull/9201
- 規模：Δ+286/-74
- 下一步：`/maigo:address-comments`
## 判斷
補測試還是反駁 reviewer
## 筆記
<!-- 手寫區 -->
細節檔格式規格見 §1a；欄位省略規則（作者／規模／下一步 何時整行不寫）與 upsert
生命週期（建立/更新/回收/孤兒偵測）也在該節。
- 🎯 下一件：Rank P0–P7，編號清單（
1. [ ]），第 1 行就是下一件事。 - ⏳ 等別人：Rank P8，checkbox 清單、無編號——球不在你手上，這區是查閱，不是待辦。
- ✅ 最近結案：Rank P9，checkbox 清單、無編號，7 天後自動清（
🧠待盤點未完成的行不清）。 - 舊版另外兩個獨立 section（收
gh抓不到的項目、收軟刪項目的那兩區）已取消：gh抓不到的項目改判抓不到（P0），併進 🎯 最上面；--drop改成把該行移進 ✅ 最近結案、狀態詞已放棄，跟其他結案行共用同一條 7 天老化規則。
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.
- 5d ago First seen · 426 lines · 112 tokens per session scan A e0b91dd75cd5
work-board is a skill published in the GitHub repository Lee-W/maigo (14 stars, last pushed yesterday), licensed MIT. It adds 112 tokens to every session and 9,467 once invoked, about $0.0006 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…