什么是 使用 T@elegrimm 群组创建智能体？

此技能旨在通过利用 Openclaw Skills 进行确定性供应，简化部署新 AI 实体的工作流程。它自动化了创建唯一 T@elegrimm 群组、建立本地工作空间以及配置智能体在无需显式提及的情况下自然响应的复杂过程。通过使用脚本优先的方法，它确保您的配置保持一致且安全。

通过集成 Openclaw Skills，开发人员可以快速扩展其智能体基础设施。该技能处理从模型发现和配置备份到基于浏览器的 T@elegrimm 群组管理自动化的所有事务，为一智能体一群组的设置提供了坚实的基础。

下载入口:https://github.com/openclaw/skills/tree/main/skills/sheetaa/create-agent-with-telegram-group

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

使用 T@elegrimm 群组创建智能体 应用场景

• 为专门的项目智能体部署其专用的通信渠道。
• 使用标准化的 USER.md、IDENTITY.md 和 SOUL.md 文件设置可重复的智能体环境。
• 将手动智能体配置迁移到结构化的、自动化的 Openclaw Skills 工作流中。
• 为需要专用 T@elegrimm 交互的 AI 编码任务建立私密、高度专注的工作空间。

1. 该技能通过读取本地配置文件发现可用的 LLM 模型以确保兼容性。
2. 它在标准化路径下初始化专用工作空间目录，以保持智能体数据隔离。
3. 通过浏览器自动化创建一个新的 T@elegrimm 群组，确保智能体具有唯一的通信端点。
4. 配置脚本更新智能体列表和绑定，同时启用无须提及回复模式以获得更好的用户体验。
5. 通过热重载或用户确认的重启应用网关设置，以激活新智能体。
6. 生成初始化文件以定义智能体的角色、使命和用户偏好。
7. 通过在新 T@elegrimm 群组中进行乒乓测试的验证循环确认部署成功。

使用 T@elegrimm 群组创建智能体 配置指南

要在 Openclaw Skills 中开始此供应工作流，请确保您的环境已准备好必要的 Python 依赖项。您可以通过运行以下命令来验证所需的脚本：

python3 scripts/provision_config.py --help
python3 scripts/init_workspace.py --help

确保您的 T@elegrimm 会话可以通过 Chrome 中继配置文件访问，以允许浏览器自动化代表您创建群组。

使用 T@elegrimm 群组创建智能体 数据架构与分类体系

该技能跨多个目录和文件组织数据以保持环境整洁。这种结构是 Openclaw Skills 管理的核心。

name: create-agent-with-telegram-group
description: Create a new OpenClaw agent and bind it to a dedicated T@elegrimm group with workspace ~/claw-. Use when the user asks for one-agent-one-group setup, T@elegrimm 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 T@elegrimm Group

Create one dedicated T@elegrimm 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-/ — workspace directory created by script
• ~/.openclaw/agents//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..
• It updates only:
  • agents.list (add/update target agent) — does NOT copy auth credentials
  • bindings (add target telegram group binding)
  • channels.telegram.groups..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.

T@elegrimm 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- and create it if missing.
3. Resolve group title:
   • custom telegram_group_title if provided
   • otherwise PascalCase(agent_name)
4. Create and bind T@elegrimm group (use resolved group title):
   • use browser automation/user-account flow (T@elegrimm 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
5. 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 --model --ch@t-id
   • this sets: agent entry, workspace, binding, and requireMention=false
6. 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
7. Bootstrap agent runtime files (required for first-run stability):
   • ensure ~/.openclaw/agents//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
8. 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 --agent-name [--with-user] [--with-identity] [--with-soul]
   • if user provided custom text, apply it after script initialization (overwrite placeholders)
9. Ensure routing validity for current schema (no invalid allowFrom entries for groups).
10. Post-provision verification:

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

11. Return completion summary with:

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

T@elegrimm 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 T@elegrimm sessions.
• If no connected Chrome tab is available, ask user to attach once, then continue.
• If T@elegrimm 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 --help for the relevant subcommand.
3. Use only discovered command forms.

Idempotency

• If ~/claw- 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 ch@t_id cannot be resolved automatically:

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

Output Template

Return concise status:

• agent:
• model:
• workspace: ~/claw-
• telegram_group: