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create-agent-with-telegram-groupcreate Agent with Telegram group 搜索

Agent Skill

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。

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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: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

简介

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。

SKILL.md

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>

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

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按下载量换算5,707

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敏感数据

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安装前确认

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