Borrowing it
Nothing to install: this file belongs to Clarity-Digital-Twin/brain-go-brrr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Clarity-Digital-Twin/brain-go-brrr/main/.cursorrulesgit clone --depth 1 https://github.com/Clarity-Digital-Twin/brain-go-brrrWrote 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.
[](https://agentmods.dev/rules/clarity-digital-twin/brain-go-brrr/cursorrules)<a href="https://agentmods.dev/rules/clarity-digital-twin/brain-go-brrr/cursorrules"><img src="https://agentmods.dev/badge/rules/clarity-digital-twin/brain-go-brrr/cursorrules.svg" alt="Measured on agentmods" height="20"></a>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 | $0.05900 | $0.05900 |
| Opus 5 | $0.02950 | $0.02950 |
| Sonnet 5 | $0.01180 | $0.01180 |
| Haiku 4.5 | $0.00590 | $0.00590 |
Grade A, and why
cursorrules 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 726 lines — stays where its author put it; the contents beside it link to each section on GitHub.
.cursorrules - Brain-Go-Brrr Project (FIXED ARCHITECTURE)
🔥🔥🔥 CRITICAL: ARCHITECTURE RULES TO PREVENT DISASTERS 🔥🔥🔥
RULE #1: NO PARALLEL IMPLEMENTATIONS EVER
NEVER CREATE DUPLICATE CODE IN experiments/ AND src/
What Went Wrong (The Disaster):
- Created TWO PARALLEL UNIVERSES that don't communicate
- experiments/ reimplemented everything from scratch
- src/ had working components that were ignored
- Result: AUROC=0.50 (complete training failure), wasted compute, confusion
The ONLY Correct Architecture:
# experiments/train_anything.py - MUST BE THIN
from brain_go_brrr.infra.data import Dataset # ALWAYS USE SRC
from brain_go_brrr.infra.ml_models import Model # NEVER REIMPLEMENT
from brain_go_brrr.domain.preprocessing import preprocess # REUSE!
# FORBIDDEN: Creating new datasets, models, preprocessing in experiments/
RULE #2: CHECK BEFORE BUILDING
- ALWAYS search src/ for existing implementations
- NEVER build without checking what exists
- ALWAYS reuse components from src/
- NEVER create "isolated" implementations
RULE #3: NORMALIZATION IS CRITICAL
- MNE outputs: 1e-5 scale (Volts)
- EEGPT expects: N(0,1) normalized
- ALWAYS normalize before model input
- NEVER trust raw sensor data
🚨 Current Architecture Status (Aug 28, 2025)
PROBLEM DISCOVERED: Parallel implementations in experiments/ and src/
- Status: BOTH FIXED with normalization
- TODO: Migrate experiments/ to use src/ components
🚨 CRITICAL WARNING: PyTorch Lightning 2.5.2 Bug
DO NOT USE PYTORCH LIGHTNING FOR TRAINING! Lightning 2.5.2 has a critical bug that causes training to hang indefinitely at:
Loading `train_dataloader` to estimate number of stepping batches
This occurs with large cached datasets (>100k samples) and CANNOT be fixed with any settings. We tried:
deterministic=False❌limit_train_batchesas integer ❌max_steps=10000❌num_sanity_val_steps=0❌fast_dev_run=True❌
SOLUTION: Use experiments/eegpt_linear_probe/train_tuab.py (pure PyTorch)
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.
- 6d ago First seen · 726 lines · 5,900 tokens per session scan A 9132fbb14e7f
cursorrules is a cursor rule published in the GitHub repository Clarity-Digital-Twin/brain-go-brrr (21 stars, last pushed 11mo ago), licensed Apache-2.0. It adds 5,900 tokens to every session, about $0.0295 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.
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