According to AlphaMoat, as of 2026-09, 赛博数字人同事制作Skill has 3,811 downloads and 16 stars — ranked #2,758 of 5,078 AI skills overall, and #546 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| SkillHub ↗ | 317 | 3.8K | 16 | — |
Platforms count differently and update at different times.
It separates work methods from communication style using chats, documents, email or manual information, retaining sources and uncertainties. Preview summaries before writing, and back up versions before updates. Collection is limited to content accessible to the account; use environment-based credentials and exclude real chats, documents and secrets from release packages. Report missing dependencies or permissions.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 3.8K | — | 16 |
| 2026-08 | 2.9K | +15.9% | 16 |
| 2026-07 | 2.5K | +38.9% | 14 |
| 2026-06 | 1.8K | +30.7% | 9 |
| 2026-05 | 1.4K | — | 5 |
| 2026-03 | 899 | — | - |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: create-colleague description: Use when turning a coworker's chats, docs, emails, and notes into a reusable AI skill that captures work methods and communication patterns. argument-hint: "[colleague-name-or-slug]" version: "1.2.1" user-invocable: true allowed-tools: Read, Write, Edit, Bash --- # 赛博同事 / Cyber Colleague
把同事的聊天、文档、邮件和笔记蒸馏成一个可复用、可迭代的 AI Skill。
Turn a coworker's chats, docs, emails, and notes into a reusable, updatable AI skill.
## 使用语言 / Language
- 默认跟随用户当前对话语言回复。
Match the user's language in the current conversation.
- 对外文档和说明尽量采用中英对照。
Prefer bilingual Chinese-English presentation for external docs and guidance.
## 适用场景 / When To Use
在这些场景下启用本 skill:
Use this skill in the following situations:
- 用户要“创建一个同事 skill / 赛博同事 / colleague skill”。
The user wants to create a colleague skill or cyber colleague.
- 用户要从聊天记录、文档、邮件、截图中提炼某位同事的工作方式。
The user wants to distill a coworker's work style from chats, docs, emails, or screenshots.
- 用户要对已生成的同事 skill 追加材料、纠正结论、重新生成。
The user wants to append new material, correct conclusions, or regenerate an existing colleague skill.
## 核心原则 / Core Principles
- 先证据,后结论。
Evidence first, conclusions second.
- 工作能力和沟通风格分开整理,但最终合并呈现。
Separate work capability from communication style, then merge them for output.
- 如果材料不足,要明确说“不足”,不要强行脑补。
If material is insufficient, say so explicitly instead of guessing.
- 更新已有 skill 时,优先增量修改并保留历史版本。
When updating an existing skill, prefer incremental changes and keep version history.
## 输入材料 / Accepted Inputs
- 飞书、钉钉、Slack 自动采集结果。
Auto-collected output from Feishu, DingTalk, or Slack.
- 飞书 JSON 导出、邮件 `.eml/.mbox`、Markdown、TXT。
Feishu JSON exports, email `.eml/.mbox`, Markdown, and TXT.
- PDF、截图、图片、直接粘贴的聊天或文档片段。
PDFs, screenshots, images, and pasted chat or document excerpts.
- 用户手动填写的角色简介、印象标签、背景信息。
Manual role summaries, impression tags, and background info from the user.
## 工具映射 / Tool Map
| 任务 Task | 工具 / 命令 Tool or Command |
| --- | --- |
| 读取 PDF、图片、文本 | `Read` |
| 写入或更新 skill 文件 | `Write` / `Edit` |
| 解析飞书 JSON | `python tools/feishu_parser.py` |
| 解析邮件 | `python tools/email_parser.py` |
| 飞书自动采集 | `python tools/feishu_auto_collector.py` |
| 飞书浏览器模式 | `python tools/feishu_browser.py` |
| 飞书 MCP 模式 | `python tools/feishu_mcp_client.py` |
| 钉钉自动采集 | `python tools/dingtalk_auto_collector.py` |
| Slack 自动采集 | `python tools/slack_auto_collector.py` |
| 创建 / 更新 / 列出 skill | `python tools/skill_writer.py` |
| 版本管理 | `python tools/version_manager.py` |
## 主流程 / Main Flow
### 1. 收集基础信息 / Collect Basic Info
至少确认这些信息:
Confirm at least these items:
1. 同事姓名或代号。
Coworker name or alias.
2. 角色简介。
Short role summary.
3. 可选标签:人格、沟通风格、团队印象。
Optional tags: personality, communication style, team impression.
### 2. 选择材料来源 / Choose Input Sources
优先给用户这些选项:
Offer these options first:
- 自动采集 / Auto-collect
- 上传文件 / Upload files
- 粘贴文本 / Paste text
- 仅基于手填信息生成 / Generate from manual info only
如果用户提供的是飞书链接,先判断走浏览器模式还是 MCP 模式。
If the user provides a Feishu link, decide between browser mode and MCP mode first.
### 3. 分成两条线分析 / Analyze In Two Tracks
**A. 工作能力 / Work Capability**
- 负责范围、系统边界、技术栈、评审重点、输出偏好。
Responsibility scope, system boundaries, stack, review focus, output preferences.
**B. 沟通与风格 / Communication And Style**
- 表达方式、决策习惯、协作方式、常见语气。
Expression style, decision habits, collaboration style, common tone.
### 4. 先预览再落盘 / Preview Before Writing
先给用户看摘要,再决定是否写入文件:
Show the user a summary before writing files:
- Work 摘要 / Work summary
- Persona 摘要 / Persona summary
- 需要保留的不确定项 / Uncertainties that should remain explicit
### 5. 写入 Skill / Write The Skill
默认写入到 `./colleagues/{slug}/`,包含:
Write to `./colleagues/{slug}/` by default, including:
- `meta.json`
- `work.md`
- `persona.md`
- `SKILL.md`
如果是更新已有 skill,先备份旧版本,再做增量改写。
If updating an existing skill, back up the previous version before making incremental edits.
## 输出结构 / Output Structure
- `work.md`:工作方法、评审习惯、技术判断。
`work.md`: work methods, review habits, technical judgment.
- `persona.md`:表达风格、沟通方式、行为偏好。
`persona.md`: communication style, tone, behavior preferences.
- `meta.json`:基础档案、来源、版本信息。
`meta.json`: profile, sources, and version info.
- `SKILL.md`:给运行时使用的完整合成版本。
`SKILL.md`: the merged runtime-facing skill document.
## 管理命令 / Management Commands
列出已有同事 skill:
List existing colleague skills:
```bash
python tools/skill_writer.py --action list --base-dir ./colleagues
```
创建新同事 skill:
Create a new colleague skill:
```bash
python tools/skill_writer.py --action create --slug <slug> --name <name> --base-dir ./colleagues
```
更新已有同事 skill:
Update an existing colleague skill:
```bash
python tools/skill_writer.py --action update --slug <slug> --base-dir ./colleagues
```
查看版本历史:
Inspect version history:
```bash
python tools/version_manager.py --action list --slug <slug> --base-dir ./colleagues
```
回滚到旧版本:
Rollback to a previous version:
```bash
python tools/version_manager.py --action rollback --slug <slug> --version <version> --base-dir ./colleagues
```
## 安全要求 / Safety Requirements
- 默认使用环境变量传入第三方凭据。
Use environment variables for third-party credentials by default.
- 不把真实聊天、文档或凭据打进发布包。
Do not package real chats, docs, or credentials into release archives.
- 浏览器模式只读取当前账号本来就能访问的内容。
Browser mode only reads content already accessible to the current account.
- 对证据不足、权限不足、依赖缺失要明确报出,不要伪装成成功。
Be explicit about insufficient evidence, missing permissions, or missing dependencies instead of pretending success.
## 成功标准 / Success Criteria
- 用户能基于最少输入创建一个结构完整的同事 skill。
The user can create a structurally complete colleague skill from minimal input.
- 新材料能增量并入已有 skill,并保留历史版本。
New material can be merged incrementally while preserving version history.
- 文档和对外说明保持中英文对照。
Docs and outward-facing guidance stay bilingual.
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
Stores agent memory and cross-skill state as a typed, constraint-checked knowledge graph.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.