#7575th of 85 in Skills, plugins and rules
trail-code
Code graph and shared team learnings for Claude Code, Cursor and Codex
- Stars
- 10k
- License
- MIT
- Last commit
- Oct 2026
- Language
- TypeScript
Missed the latest GitHub check; these facts may be older.
Overview
Trail-code (formerly graft) parses a repo with tree-sitter into a graph of files, functions and callers, and gives coding agents matching files and edit impact through hooks and MCP tools. It also saves decisions and preferences from sessions as markdown in .trail/learnings/, shared through git, and trail check compares a branch against them before a PR. The README reports 33 of 50 SWE-bench Verified issues solved with the map versus 27 without.
Who it is for: Teams using Claude Code, Cursor or Codex on shared repos
Strengths
- Code map built locally with tree-sitter, no model or API key, 23 languages
- Learnings are plain markdown in git, reviewed in PRs, no server needed
- trail check flags changes that contradict earlier team decisions before the PR
- Claude Code wired via hooks; Cursor and Codex via MCP tools and instruction files
Weaknesses
- Benchmark figures are the project's own; the SWE-bench sample is only 50 issues
- Team workspace, skills and guardrails kinds are marked as coming soon
- Day-one session mining reads Claude Code transcripts only, using Claude Sonnet
- Sends anonymous telemetry by default, opt-out
What it needs
- no GPU
- Docker
- Needs Node.js, git
- Models: Claude Code, Cursor, Codex
Also in Skills, plugins and rules
See all 85| Rank | Project | Score |
|---|---|---|
| 1 | skillsAgent skills for planning, TDD, debugging and code review | 94 out of 100 |
| 2 | eccAgents, skills, hooks and rules bundle for Claude Code, Codex and other harnesses | 94 out of 100 |
| 3 | cavemanCuts token use in coding agents with terse replies and compressed inputs | 94 out of 100 |
| #4 | ponytailSkill prompt that makes coding agents write less code and add tests | 92 out of 100 |
| #5 | impeccableDesign skill with 24 commands and a detector for AI-generated frontends | 92 out of 100 |