Introduction
Improve is a developer tool that uses a high-capability AI model to deeply analyze a codebase and produce structured improvement plans. These plans are designed to be executed by faster, cheaper models, creating an efficient two-tier workflow.
What Improve Does
- Scans a codebase to identify code quality issues, dead code, and architectural debt
- Generates structured improvement plans in Markdown with precise file references
- Prioritizes findings by impact and effort
- Produces plans consumable by AI coding agents for automated execution
- Supports incremental audits focused on recently changed files
Architecture Overview
Improve works in two phases. The audit phase feeds source files to a frontier AI model with specialized prompts that evaluate code quality, consistency, and architecture. The plan phase synthesizes findings into self-contained task descriptions with enough context for an AI coding agent to execute without additional human guidance.
Self-Hosting & Configuration
- Install via npx or npm with Node.js 18+
- Configure AI provider and model via environment variables
- Target specific directories or file patterns for focused audits
- Output plans to a directory for batch processing by agents
- Integrates with CI pipelines for periodic health checks
Key Features
- Two-tier model strategy: expensive model audits, cheap model executes
- Structured plan output with file paths, line references, and rationale
- Priority scoring based on impact and complexity
- Incremental mode for auditing only changed files
- Works with any OpenAI-compatible or Anthropic API
Comparison with Similar Tools
- SonarQube — Rule-based static analysis; Improve uses AI for deeper semantic understanding
- CodeClimate — Focuses on metrics; Improve generates actionable plans
- PR-Agent — Reviews individual PRs; Improve audits entire codebases holistically
- Sourcery — Suggests inline refactorings; Improve plans larger cross-file improvements
FAQ
Q: Does it modify code directly? A: No. Improve only produces audit reports and plans.
Q: What AI models does it support? A: Any OpenAI-compatible or Anthropic API.
Q: Can I run it in CI? A: Yes, as a CI step to track codebase health over time.
Q: How large a codebase can it handle? A: It processes files incrementally, limited mainly by API token budgets.