Generate styled PNG/SVG map images of any location with 11 customizable color themes.
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Average 4.1/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: compute_route calculates route data between locations, while generate_map renders map images. Their outputs are complementary, with compute_route explicitly designed to feed into generate_map, leaving no ambiguity about when to use each.
Both tool names follow a consistent verb_noun pattern (compute_route, generate_map). The naming style is uniform and predictable, making it easy to infer their meanings from the names alone.
With only two tools, the server feels borderline minimal. While each tool serves a clear role, the total is below the typical 3-15 tool range for a well-scoped server, making it slightly thin but not severely underdeveloped.
The server covers its core domain of map generation and route computation effectively. generate_map supports places, coordinates, markers, and routes, while compute_route provides the route data. Minor gaps exist (e.g., no standalone distance/time info), but the essential workflows are complete.
compute_routeAInspectCompute a route between two locations. Returns {coords, mode, from, to} — pass as-is into generate_map's 'route' argument. Example: from_location={label:'Tokyo Station'}, to_location={label:'Tokyo Tower'}.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | 'walking' (default) or 'driving'. | |
| to_location | Yes | Route end point. Same format as from_location. | |
| from_location | Yes | Route start point. |
| Name | Required | Description |
|---|---|---|
| to | No | Route end point. |
| from | No | Route start point. |
| mode | Yes | 'walking' or 'driving'. |
| coords | Yes | Ordered list of [lat, lng] pairs along the route. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return shape ({coords, mode, from, to}) and gives an example, which is good behavioral information. It does not mention error conditions or side effects, but for a route computation tool the core behavior is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus an example, all highly relevant and front-loaded. The purpose is stated immediately, the return contract is clear, and the example demonstrates usage without extra fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists and documents return values, so the description need not explain them. The description instead adds the key contextual insight of how the output feeds into generate_map, making the tool's place in the workflow clear. With comprehensive schema and a pointed example, nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already fully documents all three parameters including the RouteEndpoint format. The description adds a concrete example of using labels, which is helpful but not essential, keeping it at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Compute a route between two locations' with a specific verb and resource. It also names the return value and explicitly ties it to generate_map, distinguishing it from the sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong usage context by stating the output should be 'pass as-is into generate_map's route argument', indicating exactly when to use this tool relative to its sibling. It lacks an explicit 'when not to use' but the integration clue is sufficient for a single-sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_mapAInspectGenerate a styled map image. Specify 'place', 'lat'+'lng', 'markers', or 'route'. Returns a download+editor link as text, not image bytes. Example: place='Tokyo Station'.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Latitude of the map center. Must be combined with lng. | |
| lng | No | Longitude of the map center. Must be combined with lat. | |
| name | No | Map name stored in the data file. | |
| place | No | Place name to center the map on. Use this OR lat/lng, not both. | |
| route | No | Route to overlay — pass compute_route()'s result through as-is. | |
| format | No | 'png' (default) or 'svg'. | |
| layers | No | Which map layers to draw (roads, railway, POI, etc.) — see server instructions for what each preset includes. Omit for 'default'. | |
| radius | No | Circular radius in meters. Exclusive with size_ew/size_ns; omit for automatic default. | |
| markers | No | List of locations to pin on the map, e.g. [{"label": "Tokyo Station"}]. | |
| size_ew | No | Rectangular area width (east-west), meters. Pairs with size_ns; exclusive with radius. | |
| size_ns | No | Rectangular area height (north-south), meters. Pairs with size_ew. | |
| color_set | No | Background/line color theme (e.g. 'white', 'darkBlue', 'black') — see server instructions for the full list. | |
| canvas_width | No | Canvas width in pixels (default 1000). | |
| canvas_height | No | Canvas height in pixels (default 600). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the tool returns a link rather than image bytes, preventing a likely mistake. However, it doesn't mention other important behaviors such as potential geocoding side effects, file storage (the 'name' parameter hints at persistence), or any rate limits. It adds one valuable behavior note but stays minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally tight: two sentences and an example, with the core purpose stated up front. Every sentence adds value—no filler, no repetition of schema details. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 14 parameters, no annotations, and no output schema, the description plus the very detailed schema offer a fairly complete picture. The description covers the main selection modes and the non-obvious output format. It misses an explicit link to compute_route, but the schema's route description already says to pass compute_route's result. Overall, sufficient for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds a concrete example and clarifies that the input modes are alternative ways to specify the map ('Specify place, lat+lng, markers, or route'), but this is largely already conveyed by the schema descriptions. It doesn't provide significant new semantic detail beyond what the schema already contains.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with the specific action 'Generate a styled map image', clearly identifying the tool's purpose. It further specifies input modes (place, lat/lng, markers, route) and crucially distinguishes the output form ('download+editor link as text, not image bytes'), which differentiates it from a sibling like compute_route. The example solidifies clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives useful context on the different input modes and an example, implying when to use the tool. However, it does not explicitly mention alternatives or when not to use it, and despite the existence of sibling compute_route, it doesn't state that compute_route's output should be passed as the 'route' parameter. This is a gap in usage guidance.
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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