ray-project/ray

At a glance

Rank

#130 of 401

Top 32% · #29 of 56 Python repos

Checks passed

9 of 17

Full list below

Best set up for

Claude Code

Score 78.9

Needs most work for

OpenHands

Biggest fix: Reproducible dev env (+10.0 pts)

What to fix first

Showing fixes for Claude Code

1. 1
   Reproducible dev env

   Add a Makefile or devcontainer or Dockerfile so the agent can set up the project in one command.
   +11.8 pts
2. 2
   Manageable size

   If possible, split into smaller modules or carve out a focused entry path. Document where to start in AGENTS.md.
   +5.3 pts
3. 3
   Test suite

   Add a tests/ (or test/, __tests__/, spec/) directory with runnable tests. Document how to run them in AGENTS.md.
   +3.9 pts

Score for each AI agent

Each agent weighs the checks by its own docs. Under each score are its top three. How each agent is scored →

Does ray-project/ray have agent instructions?

An AGENTS.md (or CLAUDE.md) at the root tells AI coding agents how to build, test and work in the repo. A few agents also read a file of their own.

AGENTS.md / CLAUDE.md

✓AGENTS.md (new tab) · 4,319 characters

Agent-specific files

None: no GEMINI.md, .cursor/rules, .openhands/setup.sh, .aider.conf.yml or .agents/skills

Repos that have one

29 of 56 Python repos · 221 of 401 repos on the leaderboard · See examples →

How ray-project/ray compares

vs leaderboard average

6.8 pts above

Average 66.8

vs Python average

2.6 pts above

Average 71.0

Stars among Python repos

#32 of 56

One fix for the most agents: Reproducible dev env would raise the score for all 9 agents, by up to 11.9 points.

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