A shared, living collection of skill specifications for the Denolle Lab — covering AI/Copilot agents for lab tasks, seismology methods, data analysis workflows, and writing guides. All files are open, versioned, and discussable on GitHub.

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ai tools</div>

Ambient Noise Cross-Correlation Agent

AI/Copilot agent for designing, executing, and interpreting ambient seismic noise cross-correlation workflows — from waveform download through dispersion measurement.

<span class="tag">ambient-noise</span><span class="tag">cross-correlation</span><span class="tag">surface-waves</span><span class="tag">NoisePy</span><span class="tag">Copilot</span>

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research methods</div>

Ambient Noise Cross-Correlation: Standard Lab Workflow

Step-by-step protocol for computing ambient seismic noise cross-correlation functions from continuous waveform data, including pre-processing choices, stacking, QC, and dispersion measurement.

<span class="tag">ambient-noise</span><span class="tag">cross-correlation</span><span class="tag">surface-waves</span><span class="tag">NoisePy</span><span class="tag">SeisNoise</span>

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data analysis</div>

Seismic Waveform Download and Archive: FDSN Workflow

Standard workflow for bulk-downloading continuous seismic waveforms and station metadata from FDSN web services (IRIS, NCEDC, SCEDC) and archiving to local storage or AWS S3.

<span class="tag">data-download</span><span class="tag">FDSN</span><span class="tag">ObsPy</span><span class="tag">miniSEED</span><span class="tag">AWS-S3</span>

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Skills live in Denolle-Lab/lab-skills. To add or improve a skill, open an issue or start a Discussion there. Built on the academic-practice-agents framework.