cityjson_remove_materialsRemoves all materials from a CityJSON dataset, returning a new dataset_id. Use this to clean or simplify models before validation, conversion, or analysis.
Remove all materials with cjio. Returns a new dataset_id.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset_id | Yes | Dataset handle returned by cityjson_import, cityjson_open, cityjson_import_text, or another transformation tool. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does reveal that a new dataset_id is returned, which is useful, but it does not state whether the original dataset is modified, whether the operation is destructive, or what side effects removing all materials may have.
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 two short sentences with the core action first and the return value second. Every sentence earns its place, and there is no filler.
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?
For a one-parameter transformation tool with no annotations and no output schema, this description is minimally sufficient: it tells the agent what is removed and that a new dataset_id is returned. However, it lacks side-effect information and usage context, so it is not fully complete for confident selection among the many transformation siblings.
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?
Schedule coverage is 100%, and the dataset_id parameter is already described in the schema as a dataset handle from previous import/open/transformation tools. The description adds no additional parameter-level meaning, so the baseline of 3 is appropriate.
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 uses a specific verb ('Remove') and a specific resource ('all materials'), and it names the implementation ('cjio'). It is clear enough to be distinguished from the similar sibling cityjson_remove_textures, though it does not explicitly contrast the two.
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 no guidance about when to use this tool versus alternatives such as cityjson_remove_textures or other transformation tools. It states only the operation itself, leaving usage conditions to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.