Auto-Sync AI Agent Configs in CI: Never Let Your CLAUDE.md Drift Again

Your team's CLAUDE.md was last updated when you were still using Express. You've since migrated to Fastify, added three new services, and switched from Jest to Vitest. But your AI agents don't know that because nobody updated the config files.

This is config drift, and it's the silent killer of AI agent productivity. The fix? Automate it.

The GitHub Action

AI Toolkit Plus can now generate a CI workflow that keeps your configs fresh:

bash

aitoolkitplus init --agent ci

This creates .github/workflows/ai-config-sync.yml:

yaml

name: AI Config Sync
on:
  pull_request:
    branches: [main, master, develop]
  workflow_dispatch:

jobs:
  sync-configs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Install AI Toolkit Plus
        run: curl -fsSL https://aitoolkitplus.com/install.sh | bash
      - name: Generate configs
        run: aitoolkitplus init --all --json > /tmp/config-output.json
      - name: Check for changes
        run: |
          if git diff --quiet; then
            echo "Configs are up to date"
          else
            echo "Config drift detected!"
            git diff --stat
          fi
      - name: Commit updated configs
        if: # changes detected
        run: |
          git add CLAUDE.md .cursorrules GEMINI.md ...
          git commit -m "chore: sync AI agent configs"
          git push

What It Does

On every PR:

Re-analyzes your codebase (detects framework changes, new dependencies, etc.)
Regenerates all agent configs with your saved preferences
Detects drift by comparing generated output to committed files
Auto-commits updated configs if anything changed

The Viral Loop

Here's the thing about CI integrations: they're visible to the entire team.

When a developer adds FastAPI to a Python project, the next PR automatically updates:

CLAUDE.md (adds FastAPI conventions)
.cursorrules (adds Pydantic patterns)
GEMINI.md (adds endpoint documentation rules)
.github/copilot-instructions.md (adds type hint preferences)

The commit message shows up in the PR: "chore: sync AI agent configs." Every developer on the team sees it. They realize configs are being maintained. They trust their AI agents more. They write better code.

Why CI, Not Hooks

You might think: "Why not a pre-commit hook?" Three reasons:

Speed. Codebase analysis adds 2-5 seconds. Acceptable in CI, annoying in a commit hook.
Consistency. CI runs in a clean environment. No "works on my machine" issues with local Go/Node/Python versions.
Visibility. CI commits appear in PR history. The team sees when and why configs changed.

Detecting vs Fixing

You can also run in detection-only mode for stricter teams:

yaml

- name: Check config freshness
  run: |
    aitoolkitplus init --all --dry-run --json > /tmp/expected.json
    # Compare with committed configs
    # Fail the check if they diverge

This fails the CI check when configs are stale, forcing the developer to run aitoolkitplus update locally before merging. Stricter, but ensures manual review.

Combining with `.aitoolkitplus.json`

The CI action respects your project config:

json

{
  "agents": ["claude", "cursor", "copilot", "gemini"],
  "twelve_factor": true,
  "orchestrate": true
}

Commit this file, and CI always generates configs with the same flags. No need to hardcode flags in the workflow YAML.

Getting Started