strava-mcp: Skill for Claude Code

.agents/skills/spatial/SKILL.md

spatial is a skill for Claude Code from justmytwospence/strava-mcp. It costs 115 tokens per session (1,013 once invoked), scanned A, a copy of spatial, MIT.

A data-querying skill for answering questions about places and geographic data with DuckDB. It covers coordinates, distances, nearby locations, maps, and formats such as GeoJSON and Shapefile.

In plain words
What is it for?
Use it to find nearby or closest places, calculate distances, and work with spatial files such as GeoPackage, GPX, and GeoParquet.
Why use it?
It lets location questions be answered from geographic data instead of relying only on prose or visual guesses. DuckDB is a database engine that can query data files and tables.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument; installed under .agents/ (shared by several agents).

This is justmytwospence/strava-mcp's own configuration. It tells Claude Code how to work on strava-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything strava-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to justmytwospence/strava-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/justmytwospence/strava-mcp/main/.agents/skills/spatial/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/justmytwospence/strava-mcp

Made for: Claude Code.

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 spatial

README.md
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Your own site
<a href="https://agentmods.dev/skills/justmytwospence/strava-mcp/spatial"><img src="https://agentmods.dev/badge/skills/justmytwospence/strava-mcp/spatial/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 spatial

Your own site · 80×15
<a href="https://agentmods.dev/skills/justmytwospence/strava-mcp/spatial"><img src="https://agentmods.dev/badge/skills/justmytwospence/strava-mcp/spatial.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,013 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 100% copy Near-identical to another mod 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 $0.00115 $0.01013
Opus 5.5 $0.00046 $0.00405
Sonnet 5.5 $0.00023 $0.00203
Haiku 4.5 $0.00012 $0.00101

Measured 4d ago against content hash b016c8355524, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

spatial 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 4d 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.

Origin

This is a copy

100% identical to spatial — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/spatial/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are answering spatial questions using DuckDB's spatial extension and, when needed, Overture Maps as a free global data source.

Question or file: $0 Additional context: ${1:-}

Step 1 — Understand what the user needs

Classify the question:

Pattern Data source Key functions
"Find X near Y" (no user file) Overture Maps on S3 ST_Distance_Spheroid, bbox filtering
"How far between A and B" Geocode or user data ST_Distance_Spheroid
"Which points fall inside polygons" User files ST_Contains
"Analyze this GeoJSON/Shapefile/GPX" User file ST_Read, measurement functions
"Show density/hotspots" User or Overture data H3 hex binning
"Convert to GeoJSON/GeoPackage" User file COPY TO (FORMAT GDAL)
"Count buildings/roads in area" Overture Maps bbox filtering + aggregation

If the question involves real-world places, POIs, buildings, roads, or boundaries and the user hasn't provided a file, use Overture Maps — read references/overture.md for S3 paths and schema.

For spatial function syntax, read references/functions.md.

Step 2 — Write and run the query

Always start with:

LOAD spatial;
SET geometry_always_xy = true;

Add extensions as needed:

  • Overture/remote data: LOAD httpfs; CREATE SECRET (TYPE S3, PROVIDER config, REGION 'us-west-2');
  • H3 hex binning: INSTALL h3 FROM community; LOAD h3;

Key principles

bbox filtering first — When querying Overture, always filter on bbox.xmin/xmax/ymin/ymax before any spatial function. This uses Parquet predicate pushdown and avoids downloading the full dataset.

Always set geometry_always_xy = true — This ensures all spatial functions interpret coordinates as longitude, latitude (the standard for Overture, GeoJSON, and most data sources). Without it, spheroid functions assume latitude first and return wrong results.

Use spheroid functions for real-world distances — ST_Distance_Spheroid returns meters on the WGS84 ellipsoid. Plain ST_Distance uses planar coordinates and gives meaningless results for lat/lng. Important: spheroid functions (ST_Distance_Spheroid, ST_Area_Spheroid, etc.) require POINT_2D inputs, not generic GEOMETRY. Overture geometry columns are typed GEOMETRY('OGC:CRS84') and cannot be cast directly. Extract coordinates first:

ST_Point(ST_X(geometry), ST_Y(geometry))::POINT_2D

Read the full file on GitHub · 84 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. 4d ago First seen · 84 lines · 115 tokens per session scan A b016c8355524

Subscribe to this mod's changes

spatial is a skill published in the GitHub repository justmytwospence/strava-mcp (0 stars, last pushed yesterday), licensed MIT. It adds 115 tokens to every session and 1,013 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to spatial, differing in 0 lines, and is treated as a copy.

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