Telegram Crabbox E2e Proof
Skill Verified ActiveUse 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.
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.
Features
- 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
Use Cases
- 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.
Non-Goals
- 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.
Installation
npx skills add steipete/clawdisRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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