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OpenClaw Telegram assistant checklist

The fastest path to a useful private assistant is not to perfect every setting. It is to prove one clean loop: Telegram message in, OpenClaw reasoning with the right context, safe response back.

Use this checklist before changing models, hosting, persona files, and Telegram policy at the same time.

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1. Prove the local assistant works first

Start OpenClaw locally and confirm the web or CLI surface can answer a basic message.
Check which model path is active before debugging Telegram.
Keep the first test prompt simple: no file edits, no tools, no long context.
If this step fails, fix model/auth/runtime first. Telegram is not the problem yet.

2. Connect Telegram in direct chat mode

Use a direct chat first, not a group.
Verify the bot token, route, allowed user ID, and gateway status.
Send one short message and confirm OpenClaw receives the inbound event.
Only after direct chat works should you test groups, topics, or extra routing rules.

3. Add workspace context carefully

Keep AGENTS.md practical: operating rules, style, and boundaries.
Use SOUL.md for tone and assistant character, not huge project documentation.
Put stable personal preferences in USER.md and environment-specific notes in TOOLS.md.
Retest after each meaningful context change so you know what caused a behavior shift.

4. Avoid the common debugging trap

Do not change Telegram config, model credentials, prompts, and deployment target in one pass.
Separate symptoms: no inbound event, no model response, wrong persona, slow response, or blocked tool use.
Keep a tiny known-good prompt for regression tests.
Write down the working state before moving from local PC to VPS.

Where the Launch Kit helps

The Launch Kit turns this into a fuller setup path: model-choice notes, Telegram setup checklist, persona templates, deployment options, troubleshooting, and a worked example of a personal Telegram assistant.

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