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/hydah/thequeen/thequeennpx skills add hydah/thequeen --skill thequeengit clone --depth 1 https://github.com/hydah/thequeenWrote 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/hydah/thequeen/thequeen)<a href="https://agentmods.dev/skills/hydah/thequeen/thequeen"><img src="https://agentmods.dev/badge/skills/hydah/thequeen/thequeen.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 | $0.00134 | $0.04368 |
| Opus 5 | $0.00067 | $0.02184 |
| Sonnet 5 | $0.00027 | $0.00874 |
| Haiku 4.5 | $0.00013 | $0.00437 |
Grade A, and why
personal-workspace-bootstrap 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.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personal Workspace Bootstrap
Overview
将一个空仓库或已有仓库，初始化为"面向 Obsidian + AI 的个人工作台"。
这不是复制某个固定模板，而是建立一套轻量核心 + 按需模块的适应性架构。核心只有一件事：把日常工作变成可升级的长期资产。
自包含承诺：本 skill 不依赖环境中的任何其他 skill、脚本或外部工具。只要有本目录，就能从零产出完整的工作台。
两种初始化方式
方式 1：AI 辅助初始化（推荐） 在 AI 工具中触发本 skill，按 Workflow 交互式引导完成。适合想要定制化配置的场景。
方式 2：脚本一键初始化 不依赖 AI 工具，直接命令行执行：
python3 scripts/bootstrap.py /path/to/workspace --role engineer --tool claude --tool codebuddy
支持的角色：engineer、manager、creator、general（默认）。
支持的工具：claude、codebuddy、workbuddy、copilot、cursor、windsurf。
脚本是幂等的：已有文件默认不会被覆盖；bootstrap.md、index/dashboard.md 和 skills/README.md 的生成 section 会在增量装配时做最小同步。
说明：
- 不传
--tool时，脚本只负责补骨架 - 传入一个或多个
--tool时，脚本会额外创建入口文件与运行时 symlink - 如果请求接入的入口文件已存在但目标不对，脚本会显式报冲突并以非零状态退出，不会假装接入成功
- 脚本不会自动迁移已有 Markdown；已有仓库改造优先走 AI 辅助模式
- 多次运行是增量叠加，不会自动卸载此前角色带来的目录、starter skill 或运行时链接
三层资产模型
无论你的角色是什么，工作台都由三层组成：
实例层（Working Memory） ← 当前正在处理的具体事务
↓ 提炼
沉淀层（Reusable Assets） ← 从实例中总结出的可复用方法
↓ 自动化
能力层（Automated Skills） ← 把稳定流程封装成 AI 可执行的 Skill
资产升级规则（不变）：
- 第一次出现 → 写成实例（
tech/、issue/、question/等） - 第二次复用 → 提炼为
playbook/或templates/ - 第三次且流程稳定 → 升级为
skills/
角色
初始化时，先判断用户的主要角色，再决定启用哪些模块。
| 角色 | 典型工作 | 推荐重点模块 |
|---|---|---|
| Engineer | 写代码、做设计、排查 Bug、学习新技术 | tech/, issue/, projects/, playbook/ |
| Manager | 开会、做决策、跟进客户、带团队 | meeting/, decision/, customers/, review/ |
| Creator | 写作、研究、内容生产 | drafts/, research/, ideas/ |
| General | 混合角色，刚开始搭建 | 只保留最小核心，随使用自然生长 |
重要：角色不是互斥的。角色决定的是初始最小集，后续按需添加模块即可。
补充说明：scratch/ 和 todo/ 作为跨角色运行层，会对所有角色创建，以保证 bundled starter skills 第一天就可用。
Workflow
Step 1: 收集最小必要上下文
如果用户没有明确说明，先确认三件事：
- 你的主要角色是什么？（engineer / manager / creator / general）
- 当前是从零开始，还是在已有笔记/仓库上改造？
- 你最希望 AI 帮你的三件事是什么？
不要追问更多；这三点足以确定初始结构。
Step 2: 判断"从零初始化"还是"就地改造"
先扫描仓库现状：
- 是否已有
README.md或类似入口？ - 是否已有散落的 Markdown 文件？
- 是否已有某种目录结构？
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.
- 4d ago First seen · 361 lines · 134 tokens per session scan A f7e958a08e2b
personal-workspace-bootstrap is a skill published in the GitHub repository hydah/thequeen (2 stars, last pushed 4mo ago), licensed MIT. It adds 134 tokens to every session and 4,368 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
agile-product-owner
../../../product-team/agile-product-owner/skills/agile-product-owner/SKILL.md.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
subagent-delegation
Canonical protocol for delegating GSD work to native Antigravity subagents — when to delegate, how to invoke, workspace isolation modes, and the inline fallback for older IDE versions.
projects
List all managed projects with status, branch, open PRs, and open issue counts — portfolio-level view.
project-init
Scaffold an unconfigured directory into a configured pi project. Interactive, profile-driven: previews the planned writes, then writes AGENTS.md, .pi/settings.json and prompt files — optionally also a knowledge base, an openspec/ scaffold, and user-global /.pi/agent/settings.json. Use on a bare directory, or when the…