using-geoscience-skills

name	using-geoscience-skills
skill_type	meta
description	Foundation skill for the geoscience skills library. Routes user intent to the correct domain skills, slash commands, and workflow skills. Loaded automatically at session start via SessionStart hook.
version	1.0.0
author	Geoscience Skills
license	MIT
tags	["Geoscience","Skills","Routing","Discovery","Workflows","Agents"]
dependencies	[]

Using Geoscience Skills

Meta-skill for discovering, routing, and composing the geoscience skills library. This skill maps user intent to domain skills, workflow skills, slash commands, and agents.

Domain Routing Table

Match user intent keywords to the appropriate domain skill.

Keywords / Triggers	Skill	Domain
SEG-Y, seismic traces, trace headers, inline, crossline	segyio	Seismic I/O
waveform, earthquake, FDSN, seismogram, miniSEED	obspy	Seismology
surface wave, dispersion, Rayleigh, Love wave	disba	Seismology
LAS, well logs, wireline, borehole curves	lasio	Well Logs
DLIS, RP66, array logs, modern well data	dlisio	Well Logs
well analysis, curve QC, multi-well, despike	welly	Well Logs
petrophysics, Sw, porosity, formation evaluation	petropy	Petrophysics
lithology, stratigraphy, striplog, facies log	striplog	Stratigraphy
3D model, geology, implicit surface, faults	gempy	3D Modelling
fold modelling, structural frame, Loop3D	loopstructural	3D Modelling
GIS, spatial data prep, borehole to GemPy	gemgis	GIS Preprocessing
inversion, DC resistivity, magnetics, gravity, EM	simpeg	Inversion
ERT, SRT, IP, near-surface inversion	pygimli	Inversion
PDE, wave equation, finite differences, stencil	devito	Simulation
linear operator, inverse problem, sparsity	pylops	Inverse Problems
gravity, magnetic, Bouguer, upward continuation	harmonica	Potential Fields
AVO, Zoeppritz, Gassmann, fluid substitution, wavelet	bruges	Rock Physics
gridding, interpolation, spatial, Verde	verde	Spatial Analysis
variogram, kriging, GSLIB, geostatistics	geostatspy	Geostatistics
variogram fitting, scikit-learn style geostat	scikit-gstat	Geostatistics
spatial regression, GWR, GNNWR, non-stationarity, coefficient mapping	gnnwr	Spatial Regression
groundwater, time series, pumping test	pastas	Hydrology
landscape, erosion, surface processes, DEM	landlab	Surface Processes
stereonet, strike, dip, poles, structural	mplstereonet	Structural Geology
geochemistry, REE, spider diagram, ternary	pyrolite	Geochemistry
GPR, ground-penetrating radar, radargram	gprpy	Near-Surface
magnetotellurics, MT, impedance tensor	mtpy	Near-Surface
NetCDF, xarray, multi-dimensional, climate	xarray	Data Formats
3D visualization, mesh, VTK, point cloud	pyvista	Visualization
data download, sample data, cache, fetch	pooch	Utilities

Workflow Skills

Workflow skills chain multiple domain skills into end-to-end pipelines.

Workflow	Slash Command	Skill Chain
Seismic Interpretation	/seismic-workflow	segyio -> obspy -> bruges -> disba -> pyvista
Well Log Evaluation	/well-analysis	lasio/dlisio -> welly -> petropy -> striplog -> pyvista
Geological Modelling	/model-3d	gemgis -> gempy/loopstructural -> pyvista
Geophysical Inversion	/inversion-workflow	simpeg/pygimli -> verde -> pyvista
Rock Physics & AVO	/rock-physics	lasio/welly -> bruges -> segyio

Available Agents

Agent	Purpose	Typical Trigger
data-qc-reviewer	Automated data quality checks across formats	"QC my data", "check data quality"
geoscience-mentor	Guided explanations of geoscience concepts and methods	"explain", "teach me", "what is"

All 30 Domain Skills by Category

Seismic and Seismology

• segyio -- SEG-Y file I/O, trace and header access
• obspy -- seismological waveform processing, FDSN services
• disba -- surface wave dispersion (Rayleigh, Love)

Well Log Analysis

• lasio -- LAS file reading and writing
• dlisio -- DLIS/RP66 binary well log parsing
• welly -- well data analysis, curve QC, multi-well projects
• petropy -- petrophysical analysis, formation evaluation
• striplog -- lithological and stratigraphic log display

3D Geological Modelling

• gempy -- implicit 3D geological modelling
• loopstructural -- 3D modelling with fold and fault support
• gemgis -- spatial data preprocessing for GemPy

Geophysical Inversion

• simpeg -- multi-method geophysical inversion framework
• pygimli -- ERT, SRT, IP inversion with simple API
• devito -- symbolic PDE solver for wave propagation
• pylops -- linear operators for inverse problems

Potential Fields and Rock Physics

• harmonica -- gravity and magnetic data processing
• bruges -- AVO, Gassmann, wavelets, elastic moduli

Spatial Analysis and Geostatistics

• verde -- spatial gridding and interpolation
• geostatspy -- variograms, kriging (GSLIB-style)
• scikit-gstat -- geostatistics with scikit-learn API
• gnnwr -- geographically weighted neural network regression

Hydrology and Surface Processes

• pastas -- groundwater time series modelling
• landlab -- landscape evolution modelling

Structural Geology and Geochemistry

• mplstereonet -- stereonet plots for orientation data
• pyrolite -- geochemical analysis and diagrams

Near-Surface Geophysics

• gprpy -- GPR data processing
• mtpy -- magnetotelluric data analysis

Data Formats and Visualization

• xarray -- NetCDF, multi-dimensional labeled arrays
• pyvista -- 3D mesh visualization and analysis
• pooch -- data file fetching and caching

Skill Composition Rules

Chain skills when a task spans multiple stages of a geoscience workflow.

Composition Patterns

Data Loading -> Processing -> Modelling -> Visualization

1. Always start with a data I/O skill (segyio, lasio, dlisio, xarray)
2. Use processing skills for QC and transformation (welly, obspy, verde)
3. Apply domain modelling (bruges, gempy, simpeg, pygimli)
4. Finish with visualization (pyvista, matplotlib via domain skill)

When to Chain vs Use Standalone

Scenario	Approach
Single file format question	Standalone domain skill
End-to-end analysis pipeline	Workflow skill to orchestrate
Data QC across formats	data-qc-reviewer agent
Concept explanation	geoscience-mentor agent
Multi-library code generation	Chain domain skills in order

Dependency Awareness

When composing skills, respect data flow:

# Correct: segyio loads, obspy processes, bruges models
import segyio
import obspy
from bruges.reflection import zoeppritz

# Load with segyio
with segyio.open('seismic.sgy') as f:
    data = f.trace[:]

# Process with obspy (convert to Stream if needed)
# Model with bruges
Rpp = zoeppritz(vp1, vs1, rho1, vp2, vs2, rho2, theta)

When to Use This Skill

This is the discovery and routing skill. Use it when:

• Starting a new geoscience coding session and unsure which library to use
• A user request spans multiple geoscience domains
• You need to find the right slash command or workflow for a task
• Composing multiple domain skills into a pipeline
• Looking up which skill handles a specific file format or analysis type

This skill does not perform any analysis itself. It directs to the appropriate domain skill, workflow skill, or agent for execution.

Quick Decision Tree

User wants to...
  |
  +-- Load/write a file? --> Check format:
  |     SEG-Y -> segyio    LAS -> lasio    DLIS -> dlisio
  |     NetCDF -> xarray    VTK -> pyvista
  |
  +-- Process signals? --> obspy (seismology), welly (well logs)
  |
  +-- Build a model?
  |     3D geology -> gempy or loopstructural
  |     Rock physics -> bruges
  |     Inversion -> simpeg or pygimli
  |
  +-- Visualize results? --> pyvista (3D), matplotlib (2D via domain skill)
  |
  +-- Run a full pipeline? --> Use workflow skills above