Agent Guardrails acts as a critical merge gate for AI-generated code, meticulously inspecting changes before they reach production. It addresses common pain points of AI coding, such as overly broad edits, skipped tests, the introduction of new technical debt, and modifications to critical files. By defining boundaries *before* code generation, it proactively ensures AI agents adhere to specified scopes, run necessary tests, detect potential parallel abstractions or interface changes, and prevent interaction with protected code paths. This results in smaller, safer AI changes, faster code reviews, and a significant reduction in AI-related incidents, building long-term trust in AI-assisted development workflows.
Key Features
01Protected Path Enforcement: Prevents AI from touching critical files.
02Actionable Risk Summaries: Provides clear merge recommendations and remaining risk assessment.
03Drift Detection: Identifies parallel abstractions and interface changes.
041 GitHub stars
05Forced Test Validation: Requires tests to run and pass before completion.
06Bounded Scope Validation: Ensures AI only modifies allowed files.
Use Cases
01Developers integrating AI agents (Claude Code, Cursor, etc.) into real-world repositories.
02Teams and individuals aiming to prevent scope creep, untested code, or technical debt from AI-generated changes.
03Users seeking clearer validation results and reviewer-focused outputs prior to merging AI code.
