Agent skill

Shapely Compute

by parcadei in parcadei/Continuous-Claude-v3

Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates

MITAuto-check passed

Install Shapely Compute

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/shapely-compute .claude/skills/shapely-compute && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .claude/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/shapely-compute .agents/skills/shapely-compute && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .agents/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/shapely-compute .cursor/skills/shapely-compute && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .cursor/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/parcadei/Continuous-Claude-v3.git --path .claude/skills/shapely-compute

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/shapely-compute .gemini/skills/shapely-compute && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .gemini/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/shapely-compute .github/skills/shapely-compute && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .github/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install parcadei/Continuous-Claude-v3 shapely-compute --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/shapely-compute .opencode/skills/shapely-compute && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "shapely-compute" agent skill from https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/shapely-compute into .opencode/skills/shapely-compute/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shapely-compute", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: shapely-compute
GitHub stars: 3.9k
Used in: 2 other repos
Token cost: ~2k tokens
SKILL.md length: 288 words
Files: 1
Skills in repo: 141
Repo updated: Jan 26, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates

SKILL.md covers When to Use, Quick Reference, Commands and Geometry Types, plus 4 more sections
Calls uv

What it does

Shapely Compute is an agent skill from parcadei/Continuous-Claude-v3. Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows. The licence is MIT.

Example prompts

“/shapely-compute”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit d07ff4b. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Shapely Compute loads about 2k tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 288 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~29
When it runs · the whole SKILL.md, loaded when a task matches: ~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from parcadei/Continuous-Claude-v3 at commit d07ff4b, republished under its MIT licence (© parcadei). 288 words, ~2,029 tokens.

Download SKILL.mdSave it as .claude/skills/shapely-compute/SKILL.md (or your agent's skills folder).

name: shapely-compute
description: Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates
triggers: geometry, polygon, intersection, area, contains, distance between points, buffer, convex hull, centroid, WKT

Computational Geometry with Shapely

When to Use

Creating geometric shapes (points, lines, polygons)
Boolean operations (intersection, union, difference)
Spatial predicates (contains, intersects, within)
Measurements (area, length, distance, centroid)
Geometry transformations (translate, rotate, scale)
Validating and fixing invalid geometries

Quick Reference

I want to...	Command	Example
Create geometry	`create`	`create polygon --coords "0,0 1,0 1,1 0,1"`
Intersection	`op intersection`	`op intersection --g1 "POLYGON(...)" --g2 "POLYGON(...)"`
Check contains	`pred contains`	`pred contains --g1 "POLYGON(...)" --g2 "POINT(0.5 0.5)"`
Calculate area	`measure area`	`measure area --geom "POLYGON(...)"`
Distance	`distance`	`distance --g1 "POINT(0 0)" --g2 "POINT(3 4)"`
Transform	`transform translate`	`transform translate --geom "..." --params "1,2"`
Validate	`validate`	`validate --geom "POLYGON(...)"`

Commands

create

Create geometric objects from coordinates.

bash

# Point
uv run python scripts/shapely_compute.py create point --coords "1,2"

# Line (2+ points)
uv run python scripts/shapely_compute.py create line --coords "0,0 1,1 2,0"

# Polygon (3+ points, auto-closes)
uv run python scripts/shapely_compute.py create polygon --coords "0,0 1,0 1,1 0,1"

# Polygon with hole
uv run python scripts/shapely_compute.py create polygon --coords "0,0 10,0 10,10 0,10" --holes "2,2 8,2 8,8 2,8"

# MultiPoint
uv run python scripts/shapely_compute.py create multipoint --coords "0,0 1,1 2,2"

# MultiLineString (pipe-separated lines)
uv run python scripts/shapely_compute.py create multilinestring --coords "0,0 1,1|2,2 3,3"

# MultiPolygon (pipe-separated polygons)
uv run python scripts/shapely_compute.py create multipolygon --coords "0,0 1,0 1,1 0,1|2,2 3,2 3,3 2,3"

op (operations)

Boolean geometry operations.

bash

# Intersection of two polygons
uv run python scripts/shapely_compute.py op intersection \
    --g1 "POLYGON((0 0,2 0,2 2,0 2,0 0))" \
    --g2 "POLYGON((1 1,3 1,3 3,1 3,1 1))"

# Union
uv run python scripts/shapely_compute.py op union --g1 "POLYGON(...)" --g2 "POLYGON(...)"

# Difference (g1 - g2)
uv run python scripts/shapely_compute.py op difference --g1 "POLYGON(...)" --g2 "POLYGON(...)"

# Symmetric difference (XOR)
uv run python scripts/shapely_compute.py op symmetric_difference --g1 "..." --g2 "..."

# Buffer (expand/erode)
uv run python scripts/shapely_compute.py op buffer --g1 "POINT(0 0)" --g2 "1.5"

# Convex hull
uv run python scripts/shapely_compute.py op convex_hull --g1 "MULTIPOINT((0 0),(1 1),(0 2),(2 0))"

# Envelope (bounding box)
uv run python scripts/shapely_compute.py op envelope --g1 "POLYGON(...)"

# Simplify (reduce points)
uv run python scripts/shapely_compute.py op simplify --g1 "LINESTRING(...)" --g2 "0.5"

pred (predicates)

Spatial relationship tests (returns boolean).

bash

# Does polygon contain point?
uv run python scripts/shapely_compute.py pred contains \
    --g1 "POLYGON((0 0,2 0,2 2,0 2,0 0))" \
    --g2 "POINT(1 1)"

# Do geometries intersect?
uv run python scripts/shapely_compute.py pred intersects --g1 "..." --g2 "..."

# Is g1 within g2?
uv run python scripts/shapely_compute.py pred within --g1 "POINT(1 1)" --g2 "POLYGON(...)"

# Do geometries touch (share boundary)?
uv run python scripts/shapely_compute.py pred touches --g1 "..." --g2 "..."

# Do geometries cross?
uv run python scripts/shapely_compute.py pred crosses --g1 "LINESTRING(...)" --g2 "LINESTRING(...)"

# Are geometries disjoint (no intersection)?
uv run python scripts/shapely_compute.py pred disjoint --g1 "..." --g2 "..."

# Do geometries overlap?
uv run python scripts/shapely_compute.py pred overlaps --g1 "..." --g2 "..."

# Are geometries equal?
uv run python scripts/shapely_compute.py pred equals --g1 "..." --g2 "..."

# Does g1 cover g2?
uv run python scripts/shapely_compute.py pred covers --g1 "..." --g2 "..."

# Is g1 covered by g2?
uv run python scripts/shapely_compute.py pred covered_by --g1 "..." --g2 "..."

measure

Geometric measurements.

bash

# Area (polygons)
uv run python scripts/shapely_compute.py measure area --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))"

# Length (lines, polygon perimeter)
uv run python scripts/shapely_compute.py measure length --geom "LINESTRING(0 0,3 4)"

# Centroid
uv run python scripts/shapely_compute.py measure centroid --geom "POLYGON((0 0,2 0,2 2,0 2,0 0))"

# Bounds (minx, miny, maxx, maxy)
uv run python scripts/shapely_compute.py measure bounds --geom "POLYGON(...)"

# Exterior ring (polygon only)
uv run python scripts/shapely_compute.py measure exterior_ring --geom "POLYGON(...)"

# All measurements at once
uv run python scripts/shapely_compute.py measure all --geom "POLYGON((0 0,2 0,2 2,0 2,0 0))"

distance

Distance between geometries.

bash

uv run python scripts/shapely_compute.py distance --g1 "POINT(0 0)" --g2 "POINT(3 4)"
# Returns: {"distance": 5.0, "g1_type": "Point", "g2_type": "Point"}

transform

Affine transformations.

bash

# Translate (move)
uv run python scripts/shapely_compute.py transform translate \
    --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))" --params "5,10"
# params: dx,dy or dx,dy,dz

# Rotate (degrees, around centroid by default)
uv run python scripts/shapely_compute.py transform rotate \
    --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))" --params "45"
# params: angle or angle,origin_x,origin_y

# Scale (from centroid by default)
uv run python scripts/shapely_compute.py transform scale \
    --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))" --params "2,2"
# params: sx,sy or sx,sy,origin_x,origin_y

# Skew
uv run python scripts/shapely_compute.py transform skew \
    --geom "POLYGON(...)" --params "15,0"
# params: xs,ys (degrees)

validate / makevalid

Check and fix geometry validity.

bash

# Check if valid
uv run python scripts/shapely_compute.py validate --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))"
# Returns: {"is_valid": true, "type": "Polygon", ...}

# Fix invalid geometry (self-intersecting, etc.)
uv run python scripts/shapely_compute.py makevalid --geom "POLYGON((0 0,2 2,2 0,0 2,0 0))"

coords

Extract coordinates from geometry.

bash

uv run python scripts/shapely_compute.py coords --geom "POLYGON((0 0,1 0,1 1,0 1,0 0))"
# Returns: {"coords": [[0,0],[1,0],[1,1],[0,1],[0,0]], "type": "Polygon"}

fromwkt

Parse WKT and get geometry information.

bash

uv run python scripts/shapely_compute.py fromwkt "POLYGON((0 0,1 0,1 1,0 1,0 0))"
# Returns: {"type": "Polygon", "bounds": [...], "area": 1.0, ...}

Geometry Types

point - Single coordinate (x, y) or (x, y, z)
line/linestring - Sequence of connected points
polygon - Closed shape with optional holes
multipoint, multilinestring, multipolygon - Collections

Input Formats

Coordinates string: "0,0 1,0 1,1 0,1" (space-separated x,y pairs)
WKT: "POLYGON((0 0, 1 0, 1 1, 0 1, 0 0))"

Output Format

All commands return JSON with:

wkt: WKT representation of result geometry
type: Geometry type (Point, LineString, Polygon, etc.)
bounds: (minx, miny, maxx, maxy)
is_valid, is_empty: Validity flags
Measurement-specific fields (area, length, distance, etc.)

Common Use Cases

Use Case	Command
Collision detection	`pred intersects`
Point-in-polygon	`pred contains`
Area calculation	`measure area`
Buffer zones	`op buffer`
Shape combination	`op union`
Shape subtraction	`op difference`
Bounding box	`op envelope` or `measure bounds`
Simplify path	`op simplify`

/math-mode - Full math orchestration (SymPy, Z3)
/math-plot - Visualization with matplotlib

Files

Just SKILL.md in .claude/skills/shapely-compute of parcadei/Continuous-Claude-v3.

Open the folder on GitHubat commit d07ff4b

Used in 2 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in parcadei/Continuous-Claude-v3, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Shapely Compute next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Shapely Compute compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Shapely Compute this skillparcadei/Continuous-Claude-v3	3.9k	2 repos	~2k	Automated safety check: Pass	MIT	8 mo ago
Ito Computeaffaan-m/ECC	275k	1 repos	~1.7k	Automated safety check: Pass	MIT	3 days ago
Senior Computer Visiondavila7/claude-code-templates	32k	3 repos	~1.4k	Automated safety check: Pass	MIT	today
Senior Computer Visionalirezarezvani/claude-skills	28k	2 repos	~3.2k	Automated safety check: Pass	MIT	1 mo ago
GCP Computesickn33/agentic-awesome-skills	47k	2 repos	~2.6k	Automated safety check: Pass	MIT	today
Measure Before You Fixgarrytan/gbrain	31k	—	~2.5k	Automated safety check: Pass	MIT	today

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Questions about Shapely Compute

What does Shapely Compute do?

Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates. Shapely Compute is an agent skill from parcadei/Continuous-Claude-v3.

How do I install Shapely Compute in Claude Code?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a claude-code`. Or copy the skill folder (.claude/skills/shapely-compute in parcadei/Continuous-Claude-v3) into .claude/skills/shapely-compute in your project. Claude Code loads it when a task matches its description.

How do I install Shapely Compute in Codex?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a codex`. Or copy the skill folder (.claude/skills/shapely-compute in parcadei/Continuous-Claude-v3) into .agents/skills/shapely-compute in your project. Codex loads it when a task matches its description.

Can I use Shapely Compute in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add parcadei/Continuous-Claude-v3 --skill shapely-compute -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/shapely-compute, .gemini/skills/shapely-compute, .github/skills/shapely-compute and .opencode/skills/shapely-compute in your project.

What does Shapely Compute need to run?

Going by SKILL.md and its folder, Shapely Compute needs the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Shapely Compute access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Shapely Compute safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Shapely Compute use?

Shapely Compute is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Shapely Compute use?

About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Shapely Compute?

Skills that share tags, products or a category with Shapely Compute: Ito Compute (affaan-m/ECC, 275k stars), Senior Computer Vision (davila7/claude-code-templates, 32k stars), Senior Computer Vision (alirezarezvani/claude-skills, 28k stars) and GCP Compute (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Shapely Compute?

parcadei (a GitHub user) maintains it in parcadei/Continuous-Claude-v3, which has 3,940 GitHub stars. The repository holds 141 skills in this directory. The repository was last updated on January 26, 2026.

Source: parcadei/Continuous-Claude-v3 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Shapely Compute

Facts

At a glance

What it does

Example prompts

Requirements

What it can do on your machine

Tool permissions

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SKILL.md

Computational Geometry with Shapely

When to Use

Quick Reference

Commands

create

op (operations)

pred (predicates)

measure

distance

transform

validate / makevalid

coords

fromwkt

Geometry Types

Input Formats

Output Format

Common Use Cases

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