Codesight CLI reduces AI coding agent token usage by scanning codebases
What Codesight does
Codesight is a CLI tool that scans your codebase and generates a compact context pack for AI assistants, stored in a .codesight/ directory. This prevents AI coding agents like Claude Code from repeatedly exploring the same files at the start of each conversation, which typically consumes 25K–60K tokens before actual work begins.
How it works
Run npx codesight in your repository root. The tool scans TypeScript (Next.js, Express, Fastify, Hono, Nest, tRPC, React), Python (FastAPI, Django, SQLAlchemy), and Go (Gin, Gorm) stacks using AST/structured parsing instead of regex. It generates several files:
CODESIGHT.md– 1–2k token overview of architecture and key entrypointsroutes.md– all API routes with methods, paths, and tagsschema.md– database models with key fields and relationscomponents.md– UI components and propsenv.md– environment variables with usage locations and missing defaultsgraph.md– import graph with "hot" files and blast radius analysis
The blast radius analysis walks the import graph to show exactly which files, routes, and models depend on a given file, helping answer "if I change this, what breaks?" questions.
Integration
Add one line to your CLAUDE.md telling Claude to read .codesight/CODESIGHT.md and related files before exploring the tree. The tool ships with an MCP server and ready-made profiles for Claude Code, Cursor, Codex, and Copilot, so these tools treat .codesight as high-priority context.
Benchmarks
Version 1.3.1 benchmarks from real production codebases:
- SaveMRR (Hono + Drizzle, 4 workspaces, 92 files): 5,129 output tokens vs. 66,040 estimated exploration tokens (12.9× reduction)
- BuildRadar (raw HTTP + Drizzle, 53 files): 3,945 output tokens vs. 46,020 estimated exploration tokens (11.7× reduction)
- Average across these: ≈12.3× token reduction
On a TypeScript/Next backend, a long "understand + add feature + review diff" session showed 40–50K tokens of exploration avoided when Claude reads the Codesight files instead of wandering the tree.
Technical details
Single npx binary with no runtime dependencies. MIT license. Available on GitHub at https://github.com/Houseofmvps/codesight.
📖 Read the full source: r/ClaudeAI
👀 See Also
Claude Code: How to Connect Your AI-Built Frontend to a Real Backend
Claude Code builds polished frontends but often uses hardcoded data. Here are four ways to connect it to real backends: raw APIs, SDKs, CLIs, and MCP.
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A developer built a memory plugin for LLM-based agents that automatically extracts, classifies, and persists facts across sessions without explicit user commands. The system achieved 94.2% accuracy on a 52-checkpoint recall benchmark using structured markdown files instead of vector databases.