What is ragfs AGENTS.md?

Repository instructions for RAGFS, a Rust file system that finds files by meaning using text extraction, vector embeddings, and search. RAG means retrieving relevant information before an AI generates an answer.

Use it when building, testing, formatting, debugging, or running RAGFS and its command-line search tools.

It records the build, test, formatting, and run commands so changes can be checked consistently across the Rust workspace.

How Venere-Labs/ragfs configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to Venere-Labs/ragfs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/Venere-Labs/ragfs/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/Venere-Labs/ragfs

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/venere-labs/ragfs/agents-md/github.svg)](https://agentmods.dev/instructions/venere-labs/ragfs/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/venere-labs/ragfs/agents-md"><img src="https://agentmods.dev/badge/instructions/venere-labs/ragfs/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/venere-labs/ragfs/agents-md"><img src="https://agentmods.dev/badge/instructions/venere-labs/ragfs/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,174 This file is loaded in full into every session.

When invoked 1,174 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What 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 5.1	$0.01174	$0.01174
Opus 5.5	$0.00470	$0.00470
Sonnet 5.5	$0.00235	$0.00235
Haiku 4.5	$0.00117	$0.00117

Measured 1mo ago against content hash 042c9622021a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ragfs AGENTS.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 1mo 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.

AGENTS.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to Codex (Codex.ai/code) when working with code in this repository.

Build Commands

cargo build                          # Development build
cargo build --release                # Release build
cargo build -p <crate-name>          # Build specific crate

Testing

cargo test --all                     # Run all tests
cargo test -p <crate-name>           # Run tests for specific crate
cargo test -- --nocapture            # Run tests with output

Linting & Formatting

cargo fmt --all                      # Format code
cargo fmt --all -- --check           # Check formatting
cargo clippy --all-targets -- -D warnings  # Run clippy

Running

cargo run -- -v index /path/to/dir   # Index with verbose logging
cargo run -- query /path "search"    # Query the index
RUST_LOG=debug cargo run -- ...      # Debug logging

Architecture

RAGFS is a FUSE filesystem for semantic search using vector embeddings. It's organized as a Rust workspace with 10 crates plus a Python MCP server, following a pipeline pattern:

File → Extraction → Chunking → Embedding → Storage → Search

Crate hierarchy:

ragfs - CLI binary (entry: crates/ragfs/src/main.rs)
ragfs-core - Foundation traits and types (traits.rs, types.rs)
ragfs-extract - Content extraction via ExtractorRegistry
ragfs-chunker - Document chunking via ChunkerRegistry
ragfs-embed - Local embeddings using Candle (gte-small, 384-dim)
ragfs-store - Vector storage with LanceDB
ragfs-index - Pipeline orchestration and file watching
ragfs-query - Query execution
ragfs-fuse - FUSE filesystem with agent operations, safety layer, and semantic features
ragfs-python - PyO3 bindings; Haystack / LangChain / LlamaIndex adapters live under crates/ragfs-python/python/ragfs/
ragfs-mcp - Python MCP server (crates/ragfs-mcp, not a Cargo member)

ragfs-fuse modules:

filesystem.rs - Main FUSE handler, inode management, virtual directory routing
ops.rs - OpsManager for file operations with JSON feedback (.ops/)
safety.rs - SafetyManager for soft delete, audit logging, undo (.safety/)
semantic.rs - SemanticManager for AI-powered file operations (.semantic/)

Read the full file on GitHub · 117 lines

Changes

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.

1mo ago First seen · 117 lines · 1,174 tokens per session scan A 042c9622021a

Subscribe to this mod's changes

ragfs AGENTS.md is an instructions file published in the GitHub repository Venere-Labs/ragfs (14 stars, last pushed 28d ago), licensed Apache-2.0. It adds 1,174 tokens to every session, about $0.0047 per session on Opus 5.5. 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 2026-10-03.

Data and AI RAG and vectors Rust claude embeddings fuse semantic-search

ragfs AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ragfs AGENTS.mdVenere-Labs/ragfs	Instructions file	14	28d ago	Apache-2.0	A	1,174	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

ragfs: Instructions file for Codex