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feishu-agent-add飞鼠 Agent 添加

Agent Skill

feishu-agent-add 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,924

周安装

361

GitHub Stars

公开资料未说明

下载量

2,801
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:feishu-agent-add(飞鼠 Agent 添加)
来源仓库:https://github.com/cyecho-io/feishu-agent-add
安装命令:
openclaw skills install feishu-agent-add
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install feishu-agent-add

简介

当用户想要为OpenClaw添加飞书代理时,尤其是当他们说“帮我增加一个名字叫xxx,用来做xxx的飞书代理”之类的话,想要一个引导提示时,可以使用此技能。

SKILL.md

name
feishu-agent-add
description
Use this skill when users want to add a Feishu agent for OpenClaw, especially when they say things like “帮我增加一个名字叫xxx,用来做xxx的飞书agent”, want a guided prompt flow, or want a one-command way to generate the matching OpenClaw config.
license
MIT

feishu-agent-add

This skill is the conversational front end for the local script scripts/add_feishu_agent.py.

This project is designed for OpenClaw users, but the skill name intentionally stays short: feishu-agent-add.

When To Use

Use this skill when the user wants to:

  • add a new Feishu-connected OpenClaw agent
  • avoid hand-editing openclaw.json
  • configure a new agent through a few follow-up questions
  • get a ready-to-run one-line command for advanced usage

Core Rule

Do not hand-edit openclaw.json unless the user explicitly asks for manual fallback.

Prefer running:

python3 scripts/add_feishu_agent.py ...

The script is the execution core. This skill should mainly:

  1. understand the user's request
  2. ask only for missing required fields
  3. preview the plan
  4. run the script
  5. summarize the result and next steps

Required Inputs

Collect these fields before execution:

  • agent_name
  • purpose
  • agent_id

- if missing, propose one derived from the name

  • app_id
  • app_secret

These can use defaults unless the user says otherwise:

  • workspace_path

- default: ~/.openclaw/workspace-{agent_id}

  • model

- default: inherit from the current OpenClaw config

  • enable_agent_to_agent

- default: true

  • workspace_mode

- default: auto

  • init_templates

- default: true

Conversational Flow

1. Parse what the user already gave

For a request like:

帮我增加一个名字叫小红书运营,用来做内容选题和文案生成的飞书agent

extract:

  • agent_name = 小红书运营
  • purpose = 内容选题和文案生成
  • agent_id = xiaohongshu or another short slug candidate

If agent_id is missing, propose one instead of asking an open-ended question.

2. Ask the minimum follow-up questions

Only ask for the missing required fields. Prefer one compact message.

Typical follow-up:

  • proposed agent_id
  • Feishu App ID
  • Feishu App Secret

Only ask about optional fields if the user indicates they care.

3. Preview before execution

Before running the script, summarize:

  • agent name
  • agent id
  • purpose
  • workspace path
  • whether agent-to-agent collaboration will be enabled

4. Run the script

Run from the skill directory:

python3 scripts/add_feishu_agent.py \
  --agent-id <agent-id> \
  --agent-name "<agent-name>" \
  --purpose "<purpose>" \
  --app-id <app-id> \
  --app-secret <app-secret> \
  --json-output \
  --yes

Add optional flags only when needed:

  • --model <model>
  • --workspace-path <path>
  • --disable-agent-to-agent
  • --workspace-mode cli|mkdir|auto
  • --no-init-templates
  • --dry-run

Advanced User Mode

If the user prefers a single terminal command, give them a ready-to-run example instead of a manual JSON recipe.

Use this pattern:

python3 scripts/add_feishu_agent.py \
  --agent-id trader \
  --agent-name "交易小助手" \
  --purpose "股票和 ETF 分析" \
  --app-id cli_xxx \
  --app-secret secret_xxx \
  --yes

Output Expectations

After execution, summarize:

  • whether config was written successfully
  • the workspace path
  • whether starter files were initialized
  • that OpenClaw should be restarted
  • where to refine the agent identity, usually SOUL.md

If the script fails, report the concrete reason and do not improvise partial manual edits unless the user asks for that fallback.

Notes

  • The script already handles validation, backup, and config updates.
  • Prefer --dry-run first when the user asks for a preview.
  • If the user asks how to install or use this project, point them to README.md.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

80.09%
按下载量换算2,243

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install feishu-agent-add 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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