npx skills add majiayu000/claude-skill-registry --skill compare-methods-tatsuki-washimi-gwexpy-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Document Method Comparison This skill provides a procedure for creating educational sections in Jupyter Notebooks that compare two or more methods (e.g., `gwpy` vs `gwexpy`). ## Instructions 1. **Technical Analysis**: * Examine the source code of both methods to identify implementation differences. - **Averaging/Integration**: Does it downsample the data using a sliding window? (e.g., `gwpy.heterodyne`) - **Filtering**: Does it use a Low-Pass Filter (LPF) like Butterworth or FIR? (e.g., `gwexpy.lock_in`) * Compare numerical characteristics like time resolution and frequency response (aliasing). 2. **Physical/Conceptual Context**: * Check if there are differences between engineering definitions and package conventions. - Example: `gwpy.heterodyne` effectively performing "Homodyne" detection relative to the carrier frequency. * Identify the target use case for each (e.g., stationary signal vs transient analysis). 3. **Construct Comparative Sample Code**: * Create a synthetic signal that highlights the differences (e.g., a signal with rapid amplitude/phase changes). * Execute both methods on the same input signal with comparable parameters (e.g., matching the averaging stride with t
- Instructions
What does the compare_methods skill do?
ライブラリ内の類似した信号処理手法の技術的・物理的な違いを分析し、比較解説付きのノートブックセクションを作成する
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill compare-methods-tatsuki-washimi-gwexpy-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.