Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/railwayapp/cli/claude-mdgit clone --depth 1 https://github.com/railwayapp/cliWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00279 | $0.00279 |
| Opus 5 | $0.00139 | $0.00139 |
| Sonnet 5 | $0.00056 | $0.00056 |
| Haiku 4.5 | $0.00028 | $0.00028 |
Grade A, and why
cli CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Development Commands
cargo run -- <args>- Run CLI during developmentcargo test- Run testscargo lint-fix- Fix linting issues automatically (run after making changes)cargo fmt- Format code (run after making changes)cargo clippy- Check for linting issuesnix-shell- Enter dev environment with dependencies
Architecture
- Commands:
src/commands/- CLI commands using clap derives, each withexec()function - Controllers:
src/controllers/- Business logic for Railway entities (project, service, deployment) - GraphQL:
src/gql/- Generated type-safe queries/mutations for Railway API - Config:
src/config.rs- Authentication and project settings - Workspace:
src/workspace.rs- Multi-project context handling
Command System
Commands use a macro system in main.rs. The commands! macro generates routing for modules in src/commands/.
Authentication
- Project tokens via
RAILWAY_TOKENenvironment variable - User tokens via OAuth flow stored in config directory
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 28 lines · 279 tokens per session scan A b0c709cf6189
cli CLAUDE.md is an instructions file published in the GitHub repository railwayapp/cli (598 stars, last pushed 3d ago), licensed MIT. It adds 279 tokens to every session, about $0.0014 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
railway-skills AGENTS.md
Instructions for railwayapp/railway-skills, covering railway agent plugins, plugin model, skill model, reference loading pattern and architecture.
railway-skills CLAUDE.md
Instructions for railwayapp/railway-skills, a project described as: Agent skills for interacting with Railway.
spiceai copilot-instructions.md
Copilot instructions for spiceai/spiceai, covering spice.ai agent instructions, data correctness — absolute top priority, evidence — no claim without a reproduction, build, test, lint (expensive — read first) and git & prs.
spiceai AGENTS.md
AGENTS.md instructions for spiceai/spiceai, a project described as: Add a real-time analytics node to your operational database. Spice is a portable, accelerated SQL query, search, and LLM-inference engine in Rust for data-grounded AI apps and agents.
Cotal AGENTS.md
Instructions for Cotal-AI/Cotal, covering agents.md, what this is, read these first, commands and repository map.
opengeni AGENTS.md
Instructions for Cloudgeni-ai/opengeni, covering agent / automation notes (opengeni), full local stack, architecture notes, pull-request delivery across moving main and keeping these notes current.