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Unselfisheologism

io.github.Unselfisheologism/supercarto

get_maplet

Fetch real map data around a coordinate as a token-budgeted graph of named places, walkable edges, distances, and directions to answer what is nearby and how to route from A to B.

Instructions

Fetch real map data around a coordinate and return a token-budgeted topological graph: named places joined by walkable edges with distances in metres and compass directions. Use this to answer 'what is near X' and 'how do I get from A to B'. Omissions are reported, so treat a missing feature as not-shown rather than absent.

Input Schema

NameRequiredDescriptionDefault
latYesLatitude in WGS84 degrees.
lonYesLongitude in WGS84 degrees.
budgetNoToken budget for the response. Default 1024, hard cap 8192.
layersNoSemantic layers to include, e.g. ["road", "poi"]. Default all.
radiusMNoRadius in metres. Default 300. Larger costs more tokens.
returnScrNoAlso return the wire SCR in a second content block. Keep it: it is the session state a later localize() call moves within, and the agent stores it in its own RAM rather than the chat context.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses that output is token-budgeted, that results form a topological graph, and that omissions are reported so missing features should be treated as not-shown rather than absent. It does not explicitly state read-only/no side effects, but 'Fetch' strongly implies it.

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

Conciseness5/5

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

Three sentences, front-loaded with the core action and output shape, then use cases, then an important caveat about omissions. Every sentence earns its place without redundancy.

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

Completeness4/5

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

For a six-parameter graph-fetch tool with no output schema and no annotations, the description explains the returned graph, edge attributes, token budgeting, and omission semantics. It could say more about response structure or layer effects, but what is present is sufficient for an agent to understand the call's result and caveats.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all six parameters in detail, including defaults, token cap, layers, radius, and returnScr. The description mentions token budgeting but does not add parameter-level meaning beyond what the schema provides, so the baseline 3 applies.

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

Purpose4/5

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

The description gives a specific verb and resource: fetch real map data around a coordinate and return a token-budgeted topological graph. It clearly states the key output elements, named places joined by walkable edges with distances and directions, but does not explicitly distinguish this from siblings such as route or search_places.

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?

It gives explicit use cases: answering 'what is near X' and 'how do I get from A to B'. However, it provides no when-not-to-use guidance and does not name alternatives like route or search_places, leaving the sibling routing overlap unresolved.

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