Mapbox Geospatial Operations
OfficialThis skill leverages Mapbox’s geospatial expertise for robust location data manipulation and analysis, streamlining location-based workflows.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add mapbox/mapbox-agent-skills --skill mapbox-geospatial-operations -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
mapbox
Matched to the vendor's own GitHub organisation.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned mapbox/mapbox-agent-skills at f71cd72b8d.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- f71cd72b8d
- Scanned
- 2 files, 508 lines
About this skill
What it does
This skill provides geospatial operations capabilities, allowing AI agents to perform tasks like calculating distances between points, determining if a point is within a polygon, and performing other geographic calculations. It leverages Mapbox's powerful mapping tools to provide accurate and reliable results for location-based queries. The skill enables agents to reason about spatial relationships and make decisions based on geographic data.
When to use it
- Route Optimization: Determine the shortest or most efficient route between two locations, considering factors like road networks and traffic conditions.
- Geofencing: Check if a location falls within a defined geographical boundary for security or operational purposes.
- Proximity Analysis: Identify all points of interest (POIs) within a certain radius of a given location.
- Spatial Data Filtering: Filter datasets based on geographic criteria, such as finding properties located within specific zip codes.
Key capabilities
- Distance calculations between two or more coordinates.
- Point-in-polygon checks to determine if a point lies inside a defined area.
- Geographic data processing and analysis.
Example prompts
- "What is the distance in miles between San Francisco, CA and New York City, NY?"
- "Is latitude 34.0522 and longitude -118.2437 within the boundaries of Los Angeles?"
- “Find all restaurants within a 1-mile radius of 1600 Amphitheatre Parkway, Mountain View.”
Tips & gotchas
The skill requires access to Mapbox services; ensure appropriate API keys or authentication is configured for accurate results. Geographic data accuracy depends on the underlying map data provided by Mapbox.