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by ai.mapmap

reverse_geocode

Turn coordinates into the nearest places: addresses, POIs and localities with distance in metres. The inverse of geocode. Provide lat and lon; returns up to limit (default 5, max 10) results, nearest first, each with name, one-line label, lat/lon, type, address parts and distance_m, plus categories and a details object of display tags (opening_hours, website, phone, wikipedia, ...) on POI hits when the index carries them. Every result also carries bearing_deg and a spoken direction. Pass heading_deg (degrees clockwise from true north, 0 = north, 90 = east) and results are described from where the user stands — "ahead and slightly to your right, about 80 metres" — with a signed relative_bearing_deg (negative left, positive right); without a heading the phrasing falls back to cardinals ("north-east of you"), so this works with or without a compass. Add fov_deg to keep only what lies within that cone of the heading — it is the FULL width, so 90 keeps what lies within 45 degrees either side of dead ahead; anything dropped is counted in out_of_view. Prefer reading direction aloud over coordinates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude in decimal degrees (−90 to 90).
lonYesLongitude in decimal degrees (−180 to 180).
limitNoMaximum number of results (1–10, default 5). The hosted first-party index answers at most 5 nearest hits per lookup.
fov_degNoField of view: the full width in degrees of a cone centred on `heading_deg`, outside which results are dropped — it is the FULL width, so 90 keeps only what lies within 45 degrees either side of dead ahead. Needs `heading_deg` — a cone has to point somewhere. The count of results removed is reported as `out_of_view`.
heading_degNoWhich way the user is facing, in degrees **clockwise from true north** (0 = north, 90 = east, 180 = south, 270 = west). Supply it and every result is also described from the user's point of view ("just ahead on your right"); omit it and results fall back to cardinal directions ("to the north-east"), so the tool works with or without a compass.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesNearby places, nearest first.
out_of_viewNoHow many otherwise-matching places were dropped for falling outside `fov_deg`. Non-zero means there are places near the user that are simply not in front of them — say so rather than reporting nothing nearby. Always 0 when no field of view was set.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure and exceeds it. It details the output structure (name, label, lat/lon, type, address parts, distance_m, categories, details object, bearing_deg, direction), dynamic behavior (heading-based relative_bearing_deg, FOV-based out_of_view count), and even advises to 'Prefer reading direction aloud over coordinates.' This is exceptionally transparent about how the tool behaves across different inputs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with purpose, then logically flows into output details, heading behavior, FOV, and a recommendation. However, it repeats the 'FULL width' explanation of fov_deg that already exists verbatim the schema description, and it restates the default/max for limit that is also in the schema. While not wasteful, these redundancies could be trimmed without losing value. The density is justified by complexity but slightly over-lengthy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex tool with 5 parameters and rich output behavior, and the description covers everything an agent needs: input requirements, output field descriptions, edge cases (FOV without heading), fallback behavior (cardinals vs relative), and even a usability recommendation. The output schema exists but the description still explains return fields in detail, which is helpful. No gaps are evident for correct invocation and interpretation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds substantial semantic value beyond the schema. It explains the interplay between fov_deg and heading_deg (a cone must point somewhere), the full-width vs. half-width interpretation of fov_deg, the default/max for limit, and the meaning of signed relative_bearing_deg. It also clarifies that out_of_view reports dropped results, which is not in the schema property descriptions. This enriches parameter understanding significantly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Turn coordinates into the nearest places: addresses, POIs and localities with distance in metres.' It explicitly frames itself as 'The inverse of geocode,' immediately distinguishing it from the sibling tool. This gives an agent a precise understanding of what it does and how it relates to geocode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly names geocode as the inverse, which guides when to use this tool. It also explains two usage modes (with or without heading_deg) and how that changes output phrasing. However, it does not mention any other sibling tools like nearby_places, nor does it state when NOT to use this tool. The inverse reference and mode explanations provide strong contextual guidance, but exclusions are absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0
Disambiguation4/5

Most tools target a distinct action and resource pair, and descriptions are explicit about which tool fits which scenario. The closest overlaps—plan_ev_route vs cheapest_charging_along_route, and route vs plan_day vs order_stops vs optimise_routes—are mitigated by clear guidance, so an agent can usually pick correctly.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (plan_ev_route, set_palette, list_style_layers) with a consistent geo_ prefix for geometry helpers. Minor deviations like elevation, route, and matrix are short and readable but break the strict verb_noun convention.

Tool Count2/5

At 39 tools, this surface is well past the 25+ threshold and feels heavy even for a broad mapping platform. The set spans routing, geocoding, places, styles, EV/fuel, telematics, usage, and feedback, which would be easier for an agent to navigate if split into smaller domain-focused servers.

Completeness4/5

For the stated breadth, coverage is strong: routing, multi-stop planning, VRP, EV/fuel detours, geocoding, places, geometry, style lifecycle, and telematics all have workable primary paths. Minor gaps like no style deletion, no route alternatives, and no batch geocoding are present but do not create dead ends for core workflows.

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