GoKawiilNew open-source tool Farol scores pull-request risk for human approvers
A developer has released Farol, a free open-source CLI and GitHub Action that analyzes a pull request after AI code review and generates a risk score (0-100) along with a verdict of fast track, quick review, or careful review. It maps which pages, APIs, jobs and scripts are reached by the changed code using static analysis rather than AI-generated guesses, aiming to show human approvers exactly where risk lives in a diff.
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As AI agents increasingly write and review code, human approval remains the final checkpoint, and the maker argues that treating every pull request with equal scrutiny leads to skimming that can miss small but high-impact changes. By using deterministic static analysis instead of a model's judgment, Farol could offer more consistent, repeatable risk assessments than AI-based reviews, though its real-world effectiveness at catching risky merges remains to be tested at scale.
- Farol is a free, open-source CLI and GitHub Action for pull-request risk triage.
- It works after AI code review, producing a 0-100 risk score and a merge verdict (fast track, quick review, careful review).
- It relies on static analysis of call chains, dependencies, and security findings rather than AI predictions, aiming for consistent results.
Source: github.com, 2026-10-25
Published there as: “Show HN: Farol – a risk map of a pull request for the person who approves it”
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