Borrowing it
Nothing to install: this file belongs to Eden-Kramer-Lab/ripple_detection. 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/Eden-Kramer-Lab/ripple_detection/master/CLAUDE.mdgit clone --depth 1 https://github.com/Eden-Kramer-Lab/ripple_detectionWrote 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/instructions/eden-kramer-lab/ripple_detection/claude-md)<a href="https://agentmods.dev/instructions/eden-kramer-lab/ripple_detection/claude-md"><img src="https://agentmods.dev/badge/instructions/eden-kramer-lab/ripple_detection/claude-md.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 | $0.03134 | $0.03134 |
| Opus 5 | $0.01567 | $0.01567 |
| Sonnet 5 | $0.00627 | $0.00627 |
| Haiku 4.5 | $0.00313 | $0.00313 |
Grade A, and why
ripple_detection 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 8d 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 — 346 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
ripple_detection is a Python package for detecting sharp-wave ripple events (150-250 Hz) from local field potentials (LFPs) in neuroscience research. It implements detection algorithms from Karlsson et al. 2009 and Kay et al. 2016, along with other variants.
Development Commands
Setup
# Install from source (development mode with dev dependencies)
pip install -e .[dev,examples]
# Or create conda environment with all dependencies
conda env create -f environment.yml
conda activate ripple_detection
pip install -e .[dev,examples]
# Minimal install (runtime dependencies only)
pip install -e .
Testing
# Run all tests with coverage (93% coverage achieved!)
pytest --cov=ripple_detection tests/
# Run specific test module
pytest tests/test_core.py # Core signal processing tests
pytest tests/test_detectors.py # Detector integration tests
pytest tests/test_simulate.py # Simulation module tests
# Run specific test class or function
pytest tests/test_core.py::TestGetEnvelope
pytest tests/test_detectors.py::TestKayRippleDetector::test_single_channel_with_ripples
# Generate HTML coverage report
pytest --cov=ripple_detection --cov-report=html tests/
open htmlcov/index.html
# Test notebooks (as done in CI)
jupyter nbconvert --to notebook --ExecutePreprocessor.kernel_name=python3 --execute examples/detection_examples.ipynb
jupyter nbconvert --to notebook --ExecutePreprocessor.kernel_name=python3 --execute examples/test_individual_algorithm_components.ipynb
jupyter nbconvert --to notebook --ExecutePreprocessor.kernel_name=python3 --execute examples/ripple_detection_tutorial.ipynb
Code Quality
# Format code with black
black ripple_detection/ tests/
# Check formatting without modifying files
black --check ripple_detection/ tests/
# Lint code with ruff (fast, modern linter - replaces flake8)
ruff check ripple_detection/ tests/
# Auto-fix ruff issues where possible
ruff check --fix ripple_detection/ tests/
# Type check with mypy
mypy ripple_detection/
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.
- 8d ago First seen · 346 lines · 3,134 tokens per session scan A 31e0b106d4f0
ripple_detection CLAUDE.md is an instructions file published in the GitHub repository Eden-Kramer-Lab/ripple_detection (43 stars, last pushed 13d ago), licensed MIT. It adds 3,134 tokens to every session, about $0.0157 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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