start by anthropics/knowledge-work-plugins
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill start如果你看到不熟悉的占位符或需要检查已连接的工具,请参阅 CONNECTORS.md。
初始化任务和记忆系统,然后打开统一仪表板。
检查工作目录中是否存在:
TASKS.md — 任务列表CLAUDE.md — 工作记忆memory/ — 深度记忆目录dashboard.html — 可视化用户界面如果 TASKS.md 不存在: 使用标准模板创建它(参见任务管理技能)。将其放在当前工作目录中。
如果 dashboard.html 不存在: 从 复制到当前工作目录。
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${CLAUDE_PLUGIN_ROOT}/skills/dashboard.html如果 CLAUDE.md 和 memory/ 不存在: 这是一个全新的设置 — 在打开仪表板后,开始记忆引导工作流程(见下文)。将这些文件放在当前工作目录中。
不要使用 open 或 xdg-open — 在 Cowork 中,代理运行在虚拟机中,shell 打开命令无法到达用户的浏览器。相反,告诉用户:"仪表板已在 dashboard.html 准备就绪。从你的文件浏览器中打开它即可开始。"
如果一切已经初始化完成:
仪表板已打开。你的任务和记忆均已加载。
- 使用 /productivity:update 同步任务并检查记忆
- 使用 /productivity:update --comprehensive 对所有活动进行深度扫描
如果记忆尚未引导,请继续第 5 步。
仅当 CLAUDE.md 和 memory/ 尚不存在时才执行此步骤。
工作场所语言的最佳来源是用户的实际任务列表。真实的任务 = 真实的简写。
询问用户:
你在哪里保存你的待办事项或任务列表?可能是:
- 本地文件(例如,TASKS.md, todo.txt)
- 应用程序(例如 Asana, Linear, Jira, Notion, Todoist)
- 笔记文件
我将使用你的任务来学习你的工作场所简写。
一旦你获得了任务列表的访问权限:
对于每个任务项,分析其潜在的简写:
对于每个项目,以交互方式解码:
任务:"向 Todd 发送关于 Phoenix 阻塞问题的 PSR"
我看到一些术语,想确保我理解正确:
1. **PSR** - 这代表什么?
2. **Todd** - Todd 是谁?(全名,角色)
3. **Phoenix** - 这是一个项目代号吗?是关于什么的?
继续处理每个任务,只询问你尚未解码的术语。
在任务列表解码之后,提供:
你想让我对你的消息、电子邮件和文档进行全面扫描吗?
这需要更长时间,但能构建关于你工作中的人员、项目和术语更丰富的上下文。
或者我们可以坚持现有的内容,稍后再添加上下文。
如果他们选择全面扫描:
从可用的 MCP 源收集数据:
构建找到的人员、项目和术语的头脑转储。按置信度分组呈现发现结果:
根据收集到的所有信息,创建:
CLAUDE.md(工作记忆,约 50-80 行):
# 记忆
## 我
[姓名],[团队]的[角色]。
## 人员
| 谁 | 角色 |
|-----|------|
| **[昵称]** | [全名],[角色] |
## 术语
| 术语 | 含义 |
|------|---------|
| [缩写] | [全称] |
## 项目
| 名称 | 内容 |
|------|------|
| **[代号]** | [描述] |
## 偏好
- [发现的偏好]
memory/ 目录:
memory/glossary.md — 完整的解码环(缩写、术语、昵称、代号)memory/people/{name}.md — 个人档案memory/projects/{name}.md — 项目详情memory/context/company.md — 团队、工具、流程生产力系统准备就绪:
- 任务:TASKS.md (X 项)
- 记忆:X 人,X 术语,X 项目
- 仪表板:在浏览器中打开
使用 /productivity:update 保持内容最新(添加 --comprehensive 进行深度扫描)。
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If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Initialize the task and memory systems, then open the unified dashboard.
Check the working directory for:
TASKS.md — task listCLAUDE.md — working memorymemory/ — deep memory directorydashboard.html — the visual UIIfTASKS.md doesn't exist: Create it with the standard template (see task-management skill). Place it in the current working directory.
Ifdashboard.html doesn't exist: Copy it from ${CLAUDE_PLUGIN_ROOT}/skills/dashboard.html to the current working directory.
IfCLAUDE.md and memory/ don't exist: This is a fresh setup — after opening the dashboard, begin the memory bootstrap workflow (see below). Place these in the current working directory.
Do NOT use open or xdg-open — in Cowork, the agent runs in a VM and shell open commands won't reach the user's browser. Instead, tell the user: "Dashboard is ready at dashboard.html. Open it from your file browser to get started."
If everything was already initialized:
Dashboard open. Your tasks and memory are both loaded.
- /productivity:update to sync tasks and check memory
- /productivity:update --comprehensive for a deep scan of all activity
If memory hasn't been bootstrapped yet, continue to step 5.
Only do this if CLAUDE.md and memory/ don't exist yet.
The best source of workplace language is the user's actual task list. Real tasks = real shorthand.
Ask the user:
Where do you keep your todos or task list? This could be:
- A local file (e.g., TASKS.md, todo.txt)
- An app (e.g. Asana, Linear, Jira, Notion, Todoist)
- A notes file
I'll use your tasks to learn your workplace shorthand.
Once you have access to the task list:
For each task item, analyze it for potential shorthand:
For each item, decode it interactively:
Task: "Send PSR to Todd re: Phoenix blockers"
I see some terms I want to make sure I understand:
1. **PSR** - What does this stand for?
2. **Todd** - Who is Todd? (full name, role)
3. **Phoenix** - Is this a project codename? What's it about?
Continue through each task, asking only about terms you haven't already decoded.
After task list decoding, offer:
Do you want me to do a comprehensive scan of your messages, emails, and documents?
This takes longer but builds much richer context about the people, projects, and terms in your work.
Or we can stick with what we have and add context later.
If they choose comprehensive scan:
Gather data from available MCP sources:
Build a braindump of people, projects, and terms found. Present findings grouped by confidence:
From everything gathered, create:
CLAUDE.md (working memory, ~50-80 lines):
# Memory
## Me
[Name], [Role] on [Team].
## People
| Who | Role |
|-----|------|
| **[Nickname]** | [Full Name], [role] |
## Terms
| Term | Meaning |
|------|---------|
| [acronym] | [expansion] |
## Projects
| Name | What |
|------|------|
| **[Codename]** | [description] |
## Preferences
- [preferences discovered]
memory/ directory:
memory/glossary.md — full decoder ring (acronyms, terms, nicknames, codenames)memory/people/{name}.md — individual profilesmemory/projects/{name}.md — project detailsmemory/context/company.md — teams, tools, processesProductivity system ready:
- Tasks: TASKS.md (X items)
- Memory: X people, X terms, X projects
- Dashboard: open in browser
Use /productivity:update to keep things current (add --comprehensive for a deep scan).
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