dead-code-detection

Code quality analysis for Python in the age of AI coding.

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

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.

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.

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

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.

Primer for blast radius analysis and differential testing of dead code detectors and static analysis tools across pinned real-world projects

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.

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.

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.

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.