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Yarroudh

cityjson-mcp

by Yarroudh

Inspect CityJSON

cityjson_info

Retrieve metadata, object counts, types, LoDs, attribute names, transform, and extensions for a CityJSON dataset to understand its structure.

Instructions

Return metadata, object counts, types, LoDs, attribute names, transform and extensions for an opened dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesDataset handle returned by cityjson_import, cityjson_open, cityjson_import_text, or another transformation tool.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It clearly describes the read-only nature by saying 'Return', and it enumerates the output categories, which goes beyond the title. However, it does not disclose error behavior for invalid dataset_ids, whether the dataset is modified, or any restrictions on when the information is available.

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?

Single sentence, no fluff, enumerates the exact kinds of information returned. The key verb and resource are at the beginning, making the purpose immediately clear.

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?

The schema plus description fully covers how to invoke the tool (dataset_id) and what to expect (metadata, counts, types, LoDs, attributes, transform, extensions). No output schema exists, but the description gives a comprehensive preview of return contents. Minor gaps include error conditions and exact return structure, but these do not prevent correct selection or invocation.

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?

The schema description for dataset_id is thorough, specifying that it is a handle returned by specific tools, so schema coverage is 100%. The tool description doesn't add much parameter-level meaning, but it does not need to because the schema already documents the single parameter clearly.

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 uses a specific verb with a clear resource: 'Return metadata, object counts, types, LoDs, attribute names, transform and extensions for an opened dataset.' This distinguishes it from sibling tools like cityjson_list_objects or cityjson_get_object, which operate on individual objects rather than providing a dataset-level summary.

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

Usage Guidelines3/5

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

The phrase 'for an opened dataset' implies the tool should be used after cityjson_open or cityjson_import, but it does not explicitly state when to prefer this over alternatives like cityjson_list_objects or cityjson_query. There are no specific exclusion criteria or comparisons to sibling tools.

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