Trail-Code

Trail-Code describes itself as a way to turbocharge Claude Code, Cursor, Codex, Gemini and other coding agents with contextual understanding of your codebase. Its README has two parts. The first, Trail, targets repeated corrections: when you correct an agent, the lesson becomes a rule kept in your CLAUDE.md and AGENTS.md, and rules that must not be broken can get a blocking hook. Learnings that agents save after a session go into `.trail/learnings/` in the repo, are committed with the change and are read back by the next session, yours or a teammate's. `trail check` compares a change with what the team has learned before a PR.

The second part, Graft, builds a graph of your code as linked markdown files, one node per system, API or concept, saved in a `graft/` folder that is git-ignored like a local cache. The README says it rebuilds against the working tree on every query, needs no embeddings or server, and can be wired into Claude Code and other agents, including as an MCP server. Install with `npm install -g @trailhq/trail` and `trail init`; the Graft section uses the `@nanonets/graft` package name.

The README leads with numbers such as up to 4x cheaper and 3x faster, a 42% token saving and correctness rising from 54% to 66%. These are the project's own benchmark figures, and the README mixes Trail and Graft naming, so read the benchmark section and the packages you actually install carefully. A team dashboard needs signing in to a hosted service. It is MIT licensed, created in July 2026, and was last pushed on 2026-10-13. This review is based on the README and repository data; we have not run it ourselves.