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.
npx agentmods add skills/mapbox/mapbox-agent-skills/mapbox-location-groundingnpx skills add mapbox/mapbox-agent-skills --skill mapbox-location-groundinggit clone --depth 1 https://github.com/mapbox/mapbox-agent-skillsWrote 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.
[](https://agentmods.dev/skills/mapbox/mapbox-agent-skills/mapbox-location-grounding)<a href="https://agentmods.dev/skills/mapbox/mapbox-agent-skills/mapbox-location-grounding"><img src="https://agentmods.dev/badge/skills/mapbox/mapbox-agent-skills/mapbox-location-grounding.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00026 | $0.02215 |
| Opus 5 | $0.00013 | $0.01107 |
| Sonnet 5 | $0.00005 | $0.00443 |
| Haiku 4.5 | $0.00003 | $0.00221 |
Grade A, and why
mapbox-location-grounding 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mapbox Location Grounding Skill
Teaches AI assistants how to ground location-aware responses in live Mapbox data by composing MCP tools into a structured, cited answer. Use this instead of relying on training data for place names, POIs, ratings, or travel times — which are stale and prone to hallucination.
When to Use Grounding
Ground responses when the user asks about:
- "What's near [location]?" or "What's around [coordinate]?"
- "Describe this neighborhood / area"
- "Find [category] within walking/driving distance"
- "What can I do near [address]?"
- "How long does it take to get from A to B?"
- "What's within a 10-minute walk of here?"
- "How far is it between these locations?"
- Real estate, travel, mobility, or local discovery use cases
- Any question where place accuracy, recency, or travel time matters
Never answer location questions from training data alone. Always retrieve live data.
Grounding Tool Composition
Preferred: single tool call
If ground_location_tool is available, use it — it handles reverse geocoding, POI search, place details enrichment, isochrone, and a static map image in one call:
ground_location_tool(
longitude, latitude,
query: "restaurant", // optional — category or subcategory of nearby places to find
profile: "mapbox/walking", // optional — travel profile for isochrone
contours_minutes: [5, 10, 15]
)
Returns:
- Neighborhood/place name from reverse geocoding
- Nearby POIs with distances, ratings, price levels, and popularity (when available)
- Travel-time reachability from isochrone
- A static map image for visual context
- Citations for all data sources
Do not call reverse_geocode_tool, category_search_tool, place_details_tool, or isochrone_tool separately — they are already composed inside this tool.
Query parameter
The query parameter accepts category or subcategory terms — not attribute preferences:
- Supported:
"restaurant","coffee","park","Italian restaurant","EV charging station" - Not supported:
"family-friendly","fast charging","outdoor seating"— these are not filterable attributes in Mapbox data
What ships with it
1 file 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.
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.
- 5d ago First seen · 243 lines · 26 tokens per session scan A d9d1428d182b
mapbox-location-grounding is a skill published in the GitHub repository mapbox/mapbox-agent-skills (75 stars, last pushed 10d ago), licensed MIT. It adds 26 tokens to every session and 2,215 once invoked, about $0.0001 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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