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Agent Skill · 研究检索

create-agent-with-telegram-group(create Agent with Telegram group 搜索)

create-agent-with-telegram-group 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

create-agent-with-telegram-group 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 7,754。

总安装 18,129周安装 763GitHub Stars 公开资料未说明下载 6,348核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.5

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:create-agent-with-telegram-group(create Agent with Telegram group 搜索)
来源仓库:https://github.com/sheetaa/create-agent-with-telegram-group
安装命令:
openclaw skills install create-agent-with-telegram-group
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 create-agent-with-telegram-group

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

新建 OpenClaw Agent 并绑定专用 Telegram 群组通信通道。适用于远程监控或多端协同场景下的消息路由管理。自动创建工作区目录 ~/claw-<agent-name> 并初始化配置文件。需拥有 Telegram Bot API 密钥与群组管理员权限。

部署后可通过群聊指令触发 Agent 执行预定任务流程。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install create-agent-with-telegram-group;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

create-agent-with-telegram-group 怎么安装?

在终端执行 openclaw skills install create-agent-with-telegram-group。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

create-agent-with-telegram-group 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

create-agent-with-telegram-group 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

create-agent-with-telegram-group 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

create-agent-with-telegram-group 用的人多吗?

公开数据是累计安装 18,129 次,近一周安装 763 次,下载 6,348 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

create-agent-with-telegram-group 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
create-agent-with-telegram-group

create Agent with Telegram group 搜索 · 本页

18,129—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
create-agent-with-telegram-group
description
Create a new OpenClaw agent and bind it to a dedicated Telegram group with workspace ~/claw-<agent-name>. Use when the user asks for one-agent-one-group setup, Telegram group binding, or repeatable agent provisioning. Always ask which model to use, ask for essential initialization choices (USER.md/IDENTITY.md/SOUL.md), and set group reply mode to no-mention-required. Explicit user confirmation is required before any high-privilege actions: modifying openclaw.json, triggering browser automation, or restarting the gateway.

Agent Create + Dedicated Telegram Group

Create one dedicated Telegram group per agent, bind the agent to that group, and set an isolated workspace path.

Script-first Rule

Prefer bundled scripts for deterministic steps (more stable + lower token cost). Only do manual JSON editing when scripts cannot cover a special case.

Use:

  • scripts/provision_config.py for agent/config/binding/no-mention setup (with automatic backup of openclaw.json)
  • scripts/init_workspace.py for USER.md / IDENTITY.md / SOUL.md initialization

Access Scope

This skill accesses the following files on the host:

  • ~/.openclaw/openclaw.json — read (model discovery) and write (agent binding)
  • ~/.openclaw/cron/jobs.json — read-only (for job listing if needed)
  • ~/claw-<agent-name>/ — workspace directory created by script
  • ~/.openclaw/agents/<agent-id>/agent/ — directory created (no auth files copied)

Config Safety

  • scripts/provision_config.py reads and writes ~/.openclaw/openclaw.json.
  • By default it creates a backup file: ~/.openclaw/openclaw.json.bak.<timestamp>.
  • It updates only:

- agents.list (add/update target agent) — does NOT copy auth credentials - bindings (add target telegram group binding) - channels.telegram.groups.<chat_id>.requireMention=false - gateway.reload.mode only if missing (sets default hybrid)

  • The skill does NOT propagate API keys or auth tokens between agents.
  • Gateway-level auth is inherited automatically; do not manually copy auth files.

Inputs

Collect (before executing):

  • agent_name (required)
  • model (required): ask user explicitly which model to use; model options must be read live from the user’s ~/.openclaw/openclaw.json (do not hardcode examples)
  • Optional telegram_group_title override (custom group name)
  • Initialization preferences (required ask):

- whether to create/update USER.md - whether to create/update IDENTITY.md - whether to create/update SOUL.md

  • If initialization is enabled, collect content fields before writing files:

- USER.md: user name / preferred call name / language / goals / notes - IDENTITY.md: agent display name / vibe / emoji (optional) - SOUL.md: role/mission / tone / constraints (short bullet points)

Normalize agent_name:

  • Keep lowercase letters, digits, and hyphens only.
  • Replace spaces/underscores with -.
  • Use this value in paths and IDs.

Telegram group title rule:

  • If user provides telegram_group_title, use it directly.
  • If not provided, generate default title from agent name in PascalCase.

- Example: test-skill -> TestSkill, bilingual-agent -> BilingualAgent.

Workflow

  1. Read available models from ~/.openclaw/openclaw.json first, then confirm inputs with user (agent name, model, init-file preferences, optional telegram group title).
  2. Build workspace path as ~/claw-<agent-name> and create it if missing.
  3. Resolve group title:

- custom telegram_group_title if provided - otherwise PascalCase(agent_name)

  1. Create and bind Telegram group (use resolved group title):

- use browser automation/user-account flow (Telegram bot API cannot reliably create groups) - CONFIRM with user before triggering browser automation (explicit yes/no required) - if browser automation is unavailable, request the minimal manual steps and resume

  1. Create/update OpenClaw config via script (preferred):

- CONFIRM with user before modifying openclaw.json (explicit yes/no required) - python3 scripts/provision_config.py --agent-name <agent_name> --model <model> --chat-id <chat_id> - this sets: agent entry, workspace, binding, and requireMention=false

  1. Apply config and activate it:

- if hot reload is enabled, verify reload logs show applied changes - if reload is off or not applied, CONFIRM with user before restarting gateway (explicit yes/no required) - restart gateway only after user approval

  1. Bootstrap agent runtime files (required for first-run stability):

- ensure ~/.openclaw/agents/<agent-id>/agent exists - do NOT copy any auth files from other agents (this prevents credential/API key propagation) - new agents inherit authentication from the gateway's shared auth context automatically - do NOT manually copy or create auth-profiles.json, auth.json, or models.json

  1. If initialization is requested, ask user for file content fields first, then write files:

- collect required values for USER.md / IDENTITY.md / SOUL.md - then run: python3 scripts/init_workspace.py --workspace <workspace> --agent-name <agent_name> [--with-user] [--with-identity] [--with-soul] - if user provided custom text, apply it after script initialization (overwrite placeholders)

  1. Ensure routing validity for current schema (no invalid allowFrom entries for groups).
  2. Post-provision verification:

- send a test message in group and ask user to send ping - confirm agent responds without @mention

  1. Return completion summary with:

- agent name - model - workspace path - group title - chat_id - no-mention reply mode (enabled/disabled) - status and next step (if any)

Telegram Automation Rules

  • Group creation/deletion and member operations should use browser automation (user-account flow).
  • For browser flow, prefer Chrome relay profile for existing logged-in Telegram sessions.
  • If no connected Chrome tab is available, ask user to attach once, then continue.
  • If Telegram shows confirmation/captcha that cannot be automated, request one manual click, then resume.

OpenClaw Command Discovery

Do not invent OpenClaw commands.

When agent create/update command syntax is unknown:

  1. Run openclaw help.
  2. If needed, run openclaw <subcommand> --help for the relevant subcommand.
  3. Use only discovered command forms.

Idempotency

  • If ~/claw-<agent-name> already exists, reuse it.
  • If a same-name group already exists, confirm whether to reuse or create a fresh one.
  • If agent already exists, update model/binding/workdir instead of duplicating.

Reliability Checks (must do)

  • Verify requireMention=false for the bound group.
  • Verify gateway config actually applied:

- check reload mode/status logs (config hot reload applied, restarting telegram channel) - if reload is off or not applied, restart gateway and re-check logs.

  • Send one bot-originated test message to the new group, then require one live user ping.
  • Verify agent replies without @mention.
  • Do not claim success before ping -> pong verification passes.

Failure Handling

If group creation succeeds but binding fails:

  • Keep created group.
  • Report exact failed step.
  • Provide one-command resume instruction for the next run.

If chat_id cannot be resolved automatically:

  • Report that as a partial success.
  • Provide the shortest fallback step to fetch chat_id, then continue binding.

Output Template

Return concise status:

  • agent: <agent-name>
  • model: <selected-model>
  • workspace: ~/claw-<agent-name>
  • telegram_group: <title>
  • chat_id: <id or PENDING>
  • binding: <done|pending>
  • reply_without_mention: <enabled|disabled>
  • initialized_files: <USER.md, IDENTITY.md, SOUL.md or subset>
  • verification: <passed|failed>
  • next_step: <none or exact minimal action>

平台分布

OpenClaw

89.9%
按下载量换算5,707

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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