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Telegram Crabbox E2e Proof

技能 已验证 活跃

Use when reviewing, reproducing, or proving OpenClaw Telegram behavior with a real Telegram user on Crabbox, including PR review workflows that need an agent-controlled Telegram Desktop recording, TDLib user-driver commands, Convex-leased credentials, WebVNC observation, and motion-trimmed artifacts.

目的

To provide a robust and automated way to review, reproduce, or prove OpenClaw Telegram behavior in a realistic user-controlled environment, generating visual artifacts for PR reviews and bug reproduction.

功能

  • Agent-controlled Telegram user sessions
  • End-to-end testing with visual proof (recordings, screenshots)
  • TDLib and Telegram Desktop integration
  • Secure credential leasing from Convex
  • Automated session management (start, finish, status)
  • Command execution and message sending within the session

使用场景

  • Reproducing complex Telegram-related bugs.
  • Verifying OpenClaw Telegram integration behavior for pull request reviews.
  • Generating visual evidence of system behavior for documentation or debugging.
  • Automating the process of testing edge cases in a live Telegram environment.

非目标

  • Using personal Telegram accounts or adding credentials to the repository.
  • Automating direct user interactions outside of the specified testing workflow.
  • Providing general-purpose Telegram bot management.

安装

npx skills add steipete/clawdis

通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。

质量评分

已验证
100 /100
about 23 hours ago 分析

信任信号

最近提交about 24 hours ago
GitHub 所有者 steipete (opens in new tab)
星标371.6k
下载量 4.6M (opens in new tab)
许可证MIT
网站openclaw.ai(opens in new tab)
状态
查看源代码

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