Rules don't understand intent.
SonarQube pattern-matches. GitSniff reads the code and the context around it.
The differences that matter.
Three reasons teams move to GitSniff.
Reasoning beats regex.
A rule flags cyclomatic complexity. An LLM reads the function, notices it is a state machine, and approves it.
Zero infrastructure.
No server to host, no database to scale, no CI pipeline to babysit. Install the GitHub app and start.
Standards in plain English.
Write "prefer interfaces over types" in your repo instructions. No XML profile, no admin console.
The full picture.
Intent-aware review
The model considers what the function is supposed to do before flagging what looks wrong.
Filtered findings
Multi-stage quality passes drop noise before it reaches the developer.
Auto-fix patches
Instead of a rule ID and a docs link, get a diff that compiles.
Security scanners included
Bearer, Semgrep, and Trivy run as a complement, not a replacement, for AI review.
GitHub-native output
Comments on the diff, status checks on the PR. No dashboard tab to forget.
Evolving with your repo
Update instructions and every future review adapts. Static rules ship once and age.
Keep the gate. Replace the rulebook.
Point GitSniff at a repo and the first review ships in minutes. No server, no admin, no rule profile to port.