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/brainets/braina/claude-mdgit clone --depth 1 https://github.com/brainets/brainaWhat 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 | $0.01080 | $0.01080 |
| Opus 5 | $0.00540 | $0.00540 |
| Sonnet 5 | $0.00216 | $0.00216 |
| Haiku 4.5 | $0.00108 | $0.00108 |
Grade A, and why
braina 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
Braina is an AI-agent-assisted framework for analyzing complex neural interactions using information-theoretical measures on electrophysiological data (fMRI, MEG, EEG, LFP, MUA). Built at the Institut de Neurosciences de la Timone (BraiNets), Marseille.
The user may be a novice in computational neuroscience. Explain mathematical concepts (entropy, mutual information, O-information, Granger causality) simply and verify all proposed code before recommending it.
Commands
# Verify environment (all core dependencies)
uv run check_env.py
# Run the verification test suite for Frites + HOI
uv run mcp/verify_libs.py
# Launch the MCP server standalone
uv run mcp/braina_mcp.py
# Run any example script (all use uv inline dependencies)
uv run examples/frites/conn/plot_covgc.py
uv run examples/hoi/metrics/plot_oinfo.py
All scripts use uv with PEP 723 inline script metadata (# /// script blocks) for dependency management — no virtualenv setup needed.
Architecture
MCP Server (mcp/braina_mcp.py)
The central integration layer. A FastMCP server exposing 30+ tools that wrap Frites and HOI library functions with standardized file-based I/O. Each tool takes file paths as input (.npy or .nc), calls the underlying library function, and saves results. This is registered as a Claude Code MCP server (braina).
load_data/save_data are internal I/O helpers (not exposed as MCP tools) that handle the .npy vs .nc dispatch for every tool.
Tool categories:
- Data I/O:
inspect_data,read_pdf - Frites connectivity:
frites_conn_covgc,frites_conn_dfc,frites_conn_pid,frites_conn_ii,frites_conn_te,frites_conn_fit,frites_conn_spec,frites_conn_ccf - Frites workflows:
frites_wf_stats(WfStats),frites_wf_mi(WfMi),frites_wf_conn_comod(WfConnComod) - Frites simulation:
frites_sim_ar(StimSpecAR) - HOI metrics:
hoi_oinfo,hoi_gradient_oinfo,hoi_infotopo,hoi_redundancy_mmi,hoi_synergy_mmi,hoi_rsi,hoi_dtc,hoi_get_nbest_mult
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.
- yesterday First seen · 67 lines · 1,080 tokens per session scan A e91c67a28fd8
braina CLAUDE.md is an instructions file published in the GitHub repository brainets/braina (5 stars, last pushed 3mo ago), licensed BSD-3-Clause. It adds 1,080 tokens to every session, about $0.0054 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 2026-08-31.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
buildNext
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
Instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.