Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install --cask lareview
brew install puemos/tap/lareviewTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 180 |
| Forks | 25 |
| Language | Rust |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 66/100 |
| Open Issues | 15 |
| Last Updated | 2026-09-17 |
| Created | 2025-11-23 |
| Platforms | cli, rust |
| Est. Tokens | ~25k |
La Review The Code Review Workbench. LaReview is a dev-first code review workbench for complex changes. It turns a PR or diff into a structured review plan, grouped by flows and ordered by risk, so you can review with depth and understanding.
Looking for a lareview alternative? If you're comparing lareview with other ai tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Entity-level code review for Git. Graph-based risk scoring, change classification, commit untangling. 95% reca
One chat. Every agent. A universal interface for AI agents running on your computer.
Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as
100% Rust implementation of code graphRAG with blazing fast AST+FastML parsing, surrealDB backend and advanced
Flow-Like: Strongly Typed Enterprise Scale Workflows. Built for scalability, speed, seamless AI integration an
Solidity Static Analyzer that easily integrates into your editor
Explore other popular ai tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: