dead-code-detection

An Intelligent Python Code Quality Analyzer

Graph-powered code intelligence engine — indexes codebases into a knowledge graph, exposed via MCP tools for AI agents and a CLI for developers.

Open source local-first PR scanner that finds dead code, security bugs, secrets, quality regressions, and AI-code mistakes before merge. For first timers refer to https://duriantaco.github.io/skylos/repo-map/

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

A Go symbol and call-graph database backed by SQLite. Query symbols, callers, callees, blast radius, dead code, and interface implementors as structured JSON — typed code navigation for AI agents (MCP) and humans.

C# dependency analyzer

Fast Python static analysis powered by Rust. Detects dead code, security issues (including taint analysis), and code quality metrics like complexity, Halstead, maintainability, and nesting depth.

MCP local - Code intelligence tools — with broad commands that allow agents in a huge repository to do almost anything: identify the right problem → find the right file/symbol → verify the right flow → measure the scope of impact → safely refactor → check API contracts → audit health, all quickly and accurately.

X-ray vision for your codebase — semantic knowledge graph & MCP server with 16 tools that saves AI coding agents 30%+ tokens. TF-IDF search, call graphs, impact analysis, dead code detection. Works with Claude Code, Cursor & Windsurf.

A command-line tool for analyzing code metrics, complexity, and dead code in JavaScript/TypeScript projects using AST analysis. Project made for an assignment at Harbour Space Institute of Technology

Universal code structure visualization via static analysis — tree-sitter powered, no LLM

Primer for dead code detectors

Static code map generator (MAP.md + map.json) powered by tree-sitter — a Claude Code /map plugin and MCP server that gives coding agents call graphs, file outlines, and impacted-test lookups without spending tokens on parsing.

A queryable code symbol graph for multi-language monorepos — find callers, impact, dead code, and cross-file inconsistencies, every edge confidence-scored.

AI-powered TypeScript & JavaScript code analysis for complexity, security, dead code, and dependencies - 100% offline, built for MCP.

Autonomous software engineering pipeline for Claude Code: 11 stages, 64 verification rules, 17 codebase intelligence tools, 5 science-backed git analytics. Findings → PRD → verified PR with zero LLM judges.

AI-native static code intelligence CLI + MCP server — prevents collision, dead code, and security bugs before AI agents write code. 13 languages, SQLite graph model, zero LLM calls.

Bloat guard skill. Run a check, read the number, cut. Ten signals with detection commands. Executable detectors, not principles.

Point it at a Python project and get an interactive map of its code in a single HTML file: call graph, LLM-written description on every function, and flagged blind spots. Works on Django and plain Python.

Philosophy: Human-Controlled, Pattern-Driven Code Auditing.