Code Review Assistant
Catch bugs before they hit production
Automatically review pull request diffs for bugs, security vulnerabilities, performance issues, and style violations before human reviewers engage. Surfaces the critical issues that most often get missed in time-pressured manual reviews.
Claude Sonnet 5.5
for 1M tokens a month · 65% input / 35% output
Why this model
For this workload — 1M tokens a month, 65% of them input — it comes to about $6.9 a month. GPT-6.1 Sol is cheaper at $4.8, but scores 1 points lower on our editorial scale for this kind of task. The estimate includes its tokenizer, which turns the same text into about 43% more tokens than OpenAI's.
Alternative models
Implementation tips
- 1
Send only the diff, not the entire file: prefix with enough surrounding context (10–20 lines) to understand intent, but avoid bloating the prompt with unchanged code that adds cost without value.
- 2
Define a severity taxonomy in your system prompt (Critical/High/Medium/Low) and instruct the model to output only Critical and High findings — this prevents alert fatigue from trivial style comments.
- 3
Chain the review with a second pass asking the model to suggest specific code fixes for every Critical issue it found — inline suggestions close the loop from finding to resolution.