terrain-hydrology

terrain-hydrology is a skill for Claude Code, Codex from muend/geoai-skills. It costs 90 tokens per session (1,677 once invoked), scanned A, original, MIT.

A guide to analysing land shape, water flow, drainage areas, and visibility using elevation data. Elevation data can describe bare ground or surfaces that include trees and buildings, and choosing the wrong kind can produce false results.

In plain words
What is it for?
Use it to calculate slope, aspect, hillshade, streams, watersheds, catchments, viewsheds, and related terrain measurements.
Why use it?
It helps prevent errors caused by mismatched measurement units, missing elevation data, and uncorrected low spots that send simulated water in the wrong direction.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the geoai plugin — 18 skills shipped together

Good fit Use it to calculate slope, aspect, hillshade, streams, watersheds, catchments, viewsheds, and related terrain measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/muend/geoai-skills/terrain-hydrology
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 muend/geoai-skills --skill terrain-hydrology
Clone the repo
git clone --depth 1 https://github.com/muend/geoai-skills

Made for: Claude Code, Codex.

Or install geoai, the plugin that ships this one along with the rest of its 18 skills.

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 terrain-hydrology

README.md
[![agentmods](https://agentmods.dev/badge/skills/muend/geoai-skills/terrain-hydrology/github.svg)](https://agentmods.dev/skills/muend/geoai-skills/terrain-hydrology)
Your own site
<a href="https://agentmods.dev/skills/muend/geoai-skills/terrain-hydrology"><img src="https://agentmods.dev/badge/skills/muend/geoai-skills/terrain-hydrology/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 terrain-hydrology

Your own site · 80×15
<a href="https://agentmods.dev/skills/muend/geoai-skills/terrain-hydrology"><img src="https://agentmods.dev/badge/skills/muend/geoai-skills/terrain-hydrology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,677 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00090 $0.01677
Opus 5 $0.00045 $0.00839
Sonnet 5 $0.00018 $0.00335
Haiku 4.5 $0.00009 $0.00168

Measured 12d ago against content hash 391051e89b61, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

terrain-hydrology 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 12d 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.

skills/terrain-hydrology/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Terrain & Hydrology

Purpose: terrain products whose numbers are physically meaningful. The two recurring failure modes: unit mismatch (degree coordinates with meter elevations silently corrupts every derivative) and unconditioned DEMs (flow routed into spurious pits produces fragmented, fictional streams).

DEM hygiene first

Check Rule
Surface type DTM (bare earth) for hydrology/slope; DSM (with canopy/buildings) for viewshed/solar. Using a DSM for watersheds routes rivers over treetops.
Source Copernicus GLO-30 > SRTM for most global work; national LiDAR DTMs when available (see point-cloud-lidar to make your own). Record source + acquisition date.
Nodata Identify the nodata value (-9999, -32768, 3.4e38) and mask it — never let it enter statistics or fill algorithms as "very deep hole".
Voids Fill data voids (interpolation from edges) BEFORE hydrological conditioning; document filled areas.
CRS + units Reproject to a projected CRS so horizontal units = vertical units (meters). Slope from a 4326 DEM without z-factor correction is the classic silent error. If staying geographic, apply a latitude-dependent z-factor — better: don't.

Derivatives

import whitebox
wbt = whitebox.WhiteboxTools()
wbt.slope("dem.tif", "slope_deg.tif", units="degrees")
wbt.aspect("dem.tif", "aspect_deg.tif")
wbt.plan_curvature("dem.tif", "plan_curv.tif")
  • Slope: state units (degrees vs percent — 45° = 100%); Horn's method (3×3) is the standard; steeper terrain → consider resolution effects (slope flattens as cell size grows — report cell size with every slope statistic).
  • Aspect: circular variable — never average it arithmetically; use vector (sin/cos) averaging; flat cells have undefined aspect (mask, don't zero).
  • Curvature: plan (flow convergence) vs profile (flow acceleration) — pick per question.
  • Hillshade is for cartography (see cartography-geoviz), never analysis input.
  • Ruggedness/position: TRI, TPI (radius-dependent — report the radius), geomorphons for landform classification.

Read the full file on GitHub · 138 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 138 lines · 90 tokens per session scan A 391051e89b61

Subscribe to this mod's changes

terrain-hydrology is a skill published in the GitHub repository muend/geoai-skills (18 stars, last pushed 8d ago), licensed MIT. It adds 90 tokens to every session and 1,677 once invoked, about $0.0005 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 2026-08-31.