Multi-Bot Collaboration Workflow on Grok Bot

Input: writing requests, GitHub repos, product ideas → Processing: role-based bot review and collaboration → Output: safety-checked drafts, research briefs, launch plans

Who

Content creators, security practitioners, indie developers

You get

Build a team of specialized bots on Grok Bot for drafting, research, code review, and safety checks, using inter-bot messaging and human final approval to reduce public-posting risk

You need

Grok Bot

Steps

1. Create Post Guard: Pre-publish safety reviewer

   Create a new bot in Grok Bot named Post Guard. Give it a single job: review anything before it goes public under your name. Instruct it to check for API keys, tokens, personal info (including inside screenshots in terminals or URL bars), and unannounced project names. Require output format PASS / FIX / BLOCK with reasons and a cleaned-up version.

2. Split into single-purpose bots

   Do not build one giant assistant. Create separate bots per role: Social (drafts X and LinkedIn posts), Research & ideation (researches ideas, markets, competitors), Repo Vetter (reviews code before promotion), Post Guard (checks drafts before publishing). Each bot gets its own instructions, memory, and chat.

3. Configure Repo Vetter review criteria

   Set Repo Vetter's checklist: code quality, security red flags, maintainer info, license, project activity, signs of fake stars. Require output PASS / PASS WITH CAVEATS / FAIL with evidence. The author emphasizes his own repos must pass the same bar.

4. Configure Research bot for devil's advocacy and prior art

   Instruct the Research bot to argue against your ideas before you build: who already does this, who would pay, what assumptions might be wrong. Also require a "what already exists" search every time; if a product already covers your idea, adjust the angle rather than abandon it.

5. Enable direct messaging between bots

   Use Grok Bot's bot-to-bot messaging so bots talk directly. Example: Social asks Research for positioning and Repo Vetter for code review simultaneously; both return results to Social, which turns them into a launch plan. The author says no copy-paste between chats is needed.

6. Require verification against original sources, not summaries

   Direct the Research bot to read actual docs and code, not one-line summaries. Ensure every claim is backed by source. Example: the author's webmail launch copy was tightened to precise claims like "your mail is stored on your own server" and "AI is opt-in."

7. Use Page for long-lived documents

   For specs and plans you'll revisit, use Grok Bot's Page feature (a document outside chat that you keep editing together). The author suggests starting from the open questions list at the bottom each time, not from zero.

8. Create Routine for recurring tasks

   Turn repeated requests into Routines. Examples: weekday mornings, the drafting bot picks AI security news, new tools, and repos worth discussing and sends post drafts with sources; Monday mornings, one article idea with outline and first draft. Write review rules into the Routine once.

9. Disable auto-publish, keep human final approval

   Ensure no bot can post directly. All drafts are reviewed by you before publishing. When a bot wants to send a message, you get an approval card and nothing goes out without your click. The author compares this to his security product scamgate: put a check before the action, outside the model.

10. Train a Voice Guide and reuse preferences

    Have the drafting bot read 150 of your past posts and extract a voice guide (e.g., problem first, short sentences, plain words, no corporate filler). State preferences once and let bots remember them across chats. Example: after mentioning X Premium, the review bot stopped flagging long posts.

No prompt needed — just follow the steps.