geological-modelling

geological-modelling is a skill for Claude Code, Codex from SteadfastAsArt/geoscience-skills. It costs 43 tokens per session (2,716 once invoked), scanned A, original, MIT.

A workflow for building 3D geological models from GIS data, surface points, boreholes, and structural information. It prepares the data, models underground surfaces and faults, and displays the result in 3D.

In plain words
What is it for?
Use it to parse shapefiles and rasters, convert boreholes to points, transform coordinate systems, interpolate surfaces, model faults and folds, create cross-sections, and export meshes.
Why use it?
It connects scattered geological measurements to a visual underground model, including choices for simple layers, folds, faults, and unconformities.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to parse shapefiles and rasters, convert boreholes to points, transform coordinate systems, interpolate surfaces, model faults and folds, create cross-sections, and export meshes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/steadfastasart/geoscience-skills/geological-modelling
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add SteadfastAsArt/geoscience-skills --skill geological-modelling
Clone the repo
git clone --depth 1 https://github.com/SteadfastAsArt/geoscience-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin geological-modelling — /plugin install geological-modelling after adding the marketplace above.

Wrote 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.

agentmods badge for geological-modelling

README.md
[![agentmods](https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/geological-modelling/github.svg)](https://agentmods.dev/skills/steadfastasart/geoscience-skills/geological-modelling)
Your own site
<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/geological-modelling"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/geological-modelling/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for geological-modelling

Your own site · 80×15
<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/geological-modelling"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/geological-modelling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,716 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.02716
Opus 5.5 $0.00017 $0.01086
Sonnet 5.5 $0.00009 $0.00543
Haiku 4.5 $0.00004 $0.00272

Measured 1mo ago against content hash 337b5afae33b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

geological-modelling 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 1mo 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.

workflows/geological-modelling/SKILL.md · 279 lines

How it starts

The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Geological Modelling Workflow

End-to-end pipeline for building 3D geological models from spatial data, covering GIS data preparation, implicit surface modelling, and 3D visualization.

Skill Chain

gemgis              gempy / loopstructural       pyvista
[GIS Preprocessing] --> [Implicit Modelling]     --> [3D Visualization]
  |                      |                           |
  Shapefile parsing      Surface interpolation       Volume render
  Raster extraction      Fault modelling             Cross-sections
  Borehole to points     Unconformities              Mesh export
  CRS transforms         Scalar field solving        Interactive pick

Decision Points: GemPy vs LoopStructural

Criterion GemPy LoopStructural
Standard layer-cake geology Preferred Works
Complex folding (refolded folds) Limited Preferred (structural frames)
Fault networks Good Good
Built-in gravity forward model Yes No
Learning curve Gentler Steeper
Data input Points + orientations Points + orientations + fold constraints
Unconformities ERODE / ONLAP types Supported
API style Functional (gp.compute_model) Object-oriented (model.update())

Rule of thumb: Use GemPy for standard structural geology with faults and unconformities. Use LoopStructural when fold geometry is the primary control on model architecture.

Step-by-Step Orchestration

Stage 1: Spatial Data Preparation (gemgis)

import gemgis as gg
import geopandas as gpd
import rasterio

# Load geological map (shapefile)
contacts = gpd.read_file('geological_contacts.shp')
orientations = gpd.read_file('orientations.shp')

# Extract surface points from GIS contacts with DEM
with rasterio.open('dem.tif') as dem:
    # All inputs must share the DEM's projected CRS and metre units.
    contacts = contacts.to_crs(dem.crs)
    orientations = orientations.to_crs(dem.crs)
    surface_points = gg.vector.extract_xyz(contacts, dem=dem)
    orientation_pts = gg.vector.extract_xyz(orientations, dem=dem)

# Define model extent from data bounds
extent = gg.utils.set_extent(
    gdf=surface_points,
    z_min=-500, z_max=1000
)

Read the full file on GitHub · 279 lines

Changes

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.

  1. 1mo ago Changed · +28 lines 337b5afae33b
  2. 2mo ago First seen · 251 lines · 43 tokens per session scan A a7079529daa3

Subscribe to this mod's changes

geological-modelling is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (73 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 2,716 once invoked, about $0.0002 per session on Opus 5.5. 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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