shapely

shapely is a skill for Claude Code from tondevrel/scientific-agent-skills. It costs 105 tokens per session (2,767 once invoked), scanned A, original, MIT.

A Python library for working with flat, two-dimensional shapes such as points, lines, and polygons. It uses GEOS, a widely used geometry engine.

In plain words
What is it for?
Use it to measure areas and distances, find intersections or unions, test whether shapes overlap or contain one another, and clean invalid geometry.
Why use it?
It removes the need to implement common shape calculations and relationship checks yourself.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the scientific-agent-skills plugin — 55 skills, 2 commands, 1 MCP server shipped together

Good fit Use it to measure areas and distances, find intersections or unions, test whether shapes overlap or contain one another, and clean invalid geometry.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tondevrel/scientific-agent-skills/shapely
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 tondevrel/scientific-agent-skills --skill shapely
Clone the repo
git clone --depth 1 https://github.com/tondevrel/scientific-agent-skills

Made for: Claude Code.

Or install scientific-agent-skills, the plugin that ships this one along with the rest of its 55 skills, 2 commands, 1 MCP server.

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 shapely

README.md
[![agentmods](https://agentmods.dev/badge/skills/tondevrel/scientific-agent-skills/shapely/github.svg)](https://agentmods.dev/skills/tondevrel/scientific-agent-skills/shapely)
Your own site
<a href="https://agentmods.dev/skills/tondevrel/scientific-agent-skills/shapely"><img src="https://agentmods.dev/badge/skills/tondevrel/scientific-agent-skills/shapely/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 shapely

Your own site · 80×15
<a href="https://agentmods.dev/skills/tondevrel/scientific-agent-skills/shapely"><img src="https://agentmods.dev/badge/skills/tondevrel/scientific-agent-skills/shapely.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 105 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,767 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 $0.00105 $0.02767
Opus 5 $0.00053 $0.01384
Sonnet 5 $0.00021 $0.00553
Haiku 4.5 $0.00011 $0.00277

Measured 9d ago against content hash d0316a995fa7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

shapely 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 9d 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/shapely/SKILL.md · 347 lines

How it starts

The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Shapely - Planar Geometry

Shapely is the engine behind GeoPandas and many other GIS tools. It focuses on the geometry itself: calculating intersections, unions, distances, and checking spatial relationships (like "is this point inside this polygon?").

When to Use

  • Precise manipulation of 2D geometric shapes.
  • Performing set-theoretic operations (Intersection, Union, Difference).
  • Checking spatial predicates (Contains, Within, Intersects, Touches).
  • Cleaning and validating "dirty" geometry (fixing self-intersections).
  • Calculating geometric properties (Area, Length, Centroid, Bounds).
  • Generating buffers or simplifying complex lines.
  • Linear referencing (finding points along a line).

Reference Documentation

Official docs: https://shapely.readthedocs.io/
GEOS (Engine): https://libgeos.org/
Search patterns: shapely.geometry, shapely.ops.unary_union, shapely.validation.make_valid

Core Principles

Geometric Objects

Objects are immutable. Once created, you don't change them; you perform an operation that returns a new object.

  • Points: 0-dimensional.
  • LineStrings: 1-dimensional curves.
  • Polygons: 2-dimensional surfaces with optional holes.

Cartesian Geometry

Shapely operates in a Cartesian plane. It does not know about Earth's curvature, latitudes, or longitudes. Distance is sqrt(dx² + dy²).

Vectorization (Shapely 2.0+)

Modern Shapely supports vectorized operations on NumPy arrays of geometry objects, making it significantly faster than older versions.

Quick Reference

Installation

pip install shapely numpy

Standard Imports

import numpy as np
from shapely import Point, LineString, Polygon, MultiPoint, MultiPolygon
from shapely import ops, wkt, wkb
import shapely

Basic Pattern - Creation and Analysis

from shapely.geometry import Point, Polygon

# 1. Create objects
p = Point(0, 0)
poly = Polygon([(0, 0), (2, 0), (2, 2), (0, 2)])

# 2. Check relationships
is_inside = p.within(poly) # True
is_on_border = p.touches(poly) # False (interior counts as within)

# 3. Calculate
print(f"Area: {poly.area}")
print(f"Distance: {p.distance(Point(10, 10))}")

Read the full file on GitHub · 347 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. 9d ago First seen · 347 lines · 105 tokens per session scan A d0316a995fa7

Subscribe to this mod's changes

shapely is a skill published in the GitHub repository tondevrel/scientific-agent-skills (21 stars, last pushed 7mo ago), licensed MIT. It adds 105 tokens to every session and 2,767 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 2026-08-30.

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