AI-powered code review and release prep for your CI/CD pipeline, powered by Attune AI and Claude.
Smart tier routing automatically optimizes LLM costs (34-86% savings) while maintaining quality.
name: Attune Code Review
on: [pull_request]
jobs:
review:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 2
- uses: Smart-AI-Memory/attune-ai-action@v1
with:
workflow: code-review
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}name: Attune Release Prep
on:
push:
tags: ['v*']
jobs:
release-prep:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- uses: Smart-AI-Memory/attune-ai-action@v1
with:
workflow: release-prep
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
fail_on_critical: 'true'| Input | Required | Default | Description |
|---|---|---|---|
workflow |
Yes | - | code-review or release-prep |
anthropic_api_key |
Yes | - | Your Anthropic API key |
python_version |
No | 3.12 |
Python version |
attune_version |
No | latest |
Attune AI version |
tier_strategy |
No | auto |
Cost tier: auto, cheap, capable, premium |
fail_on_critical |
No | true |
Fail action on critical issues |
config |
No | - | Path to attune config file |
| Output | Description |
|---|---|
report |
Path to generated report |
summary |
Brief summary of findings |
issues_found |
Number of issues found |
cost_saved |
Estimated cost savings from tier routing |
Attune AI routes prompts through smart tiers (CHEAP -> CAPABLE -> PREMIUM), only escalating when complexity requires it. In CI, this means routine reviews use cheaper models while critical security findings get premium attention — saving 34-86% vs. using the most expensive model for everything.
Set tier_strategy to control this:
auto(default) — Attune decides based on complexitycheap— minimize cost, good for quick checkscapable— balanced quality and costpremium— maximum quality, use for release-critical reviews
Apache 2.0 — same as Attune AI.