Advanced Patterns — Vibe Coding, Tool Composition

~14 min · gemini, advanced, vibe-coding, automation

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Where Gemini's culture leans

Gemini's design culture is heavier on autonomous "vibe coding" — give a high-level goal, let the agent plan and execute aggressively. The pattern: tighter sandbox, looser approval, longer goals. Combined with the 1M context, you can hand Gemini "modernize this Express 4 codebase to Express 5" and let it run.

Three advanced patterns: (1) multi-tool composition — chain extension tools, MCP servers, and Skills inside one prompt; (2) autonomous batching — Gemini decomposes a big task into a fan-out of sub-tasks (similar to Claude Code's /batch but with different conventions); (3) headless GitHub Actions — Gemini ships an official Action for PR review and automated maintenance.

Code

Multi-tool prompt with sandbox·bash

gemini --sandbox --model gemini-2.5-pro \
  "Read all files in src/ (use the 1M context).
   Generate an OpenAPI 3.1 spec from the route handlers.
   Use the cloud-run extension to deploy a docs site
     showing the spec at internal-api-docs.example.com.
   Send a Slack notification to #api-changes via the
     Slack MCP when done."

Gemini GitHub Action·yaml

# .github/workflows/gemini-review.yml
name: Gemini PR Review
on: { pull_request: { types: [opened, synchronize] } }
jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with: { fetch-depth: 0 }
      - uses: google-gemini/gemini-cli-action@v1
        with:
          gemini_api_key: ${{ secrets.GEMINI_API_KEY }}
          mode: review
          prompt: |
            Review for bugs, security, perf, style violations
            against GEMINI.md. Format:
            [SEVERITY] desc (file:line)

External links

Exercise

Run an ambitious autonomous task in Gemini: sandbox on, 1M-context model, at least one extension or MCP server. Set a clear goal, walk away, come back to review. Note where the agent went off-track and where it nailed it.