trailhq/Trail-Code

Local-first engineering memory and large-scale polyglot graph search for Codex, Claude, Cursor, Copilot, and the next agent you try.

Codebase Context gives AI agents understanding of your codebase through semantic code search, team conventions, patterns, and memory, so they use fewer tokens, spend less time, and produce better, more familiar output.

Make your coding agents 10x smarter

Find out what your coding agents already know. Docmancer indexes the memory, rules, and instructions Claude Code, Codex, Cursor, and Gemini wrote on your machine, then carries the durable parts to every agent. It is local-first and under MIT license.

Tasks, docs, specs and decisions for AI coding agents, as markdown in your repo. Keeps the agent from breaking architectural decisions you already made.

Spec-driven development and context engineering for Claude Code, Cursor, Codex, and GitHub Copilot — backed by project context in Git.

Persistent code memory for AI coding agents, kept in your project on your machine. Gives Claude Code, Cursor, Cline, Hermes-Agent and any MCP client the files that matter for each prompt, learns which files you use together, and publishes every benchmark with its misses.

Persistent, searchable engineering memory for AI coding agents. Saves ~50% tokens and ~30% time while planning

Carry context across coding agents/editors/IDEs - Cursor/Windsurf/Claude Code/Antigravity