List all 114 terrain presets, optionally filtered by category, to select presets for generative terrain and scene design.
List all 114 terrain presets, optionally filtered by category (sky, profile, clouds, water, river, path, shore, field, rock, treeline, celestial, fog, starfield, cliff-face, snowfield, building, bridge, reflection, haze, fence, boat).
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter by category. |
Changes observed during successful MCP inspections.
v0.5.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It does convey the result size (114 items), which is genuinely useful for planning, but it omits whether all results come back in one unpaginated response, what a preset record contains (id, name, parameters?), and whether presets are read-only references that can be passed to design_add_sky and similar add_* tools. For a zero-annotation tool this leaves meaningful behavioral gaps.
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?
It is a single front-loaded sentence, which is good, but roughly 70% of its length is a verbatim copy of the schema's 21 enum values. That bulk earns nothing, since an agent reads the enum from the schema anyway.
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-optional-param read-only list tool this is close to sufficient, but with no output schema and no annotations the description should say what a preset object looks like or how the returned presets are consumed by the design_add_* tools. The near-total absence of that linkage leaves the definition merely adequate.
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 description coverage is 100% and the single parameter is a fully enumerated string, so the schema already does the work. The description restates the identical enum verbatim, adding no syntax, defaulting, or matching semantics beyond what is structured.
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?
States a specific verb and resource ('List all 114 terrain presets') plus the exact filter dimension, so an agent knows precisely what it returns. It does not distinguish itself from nearby list siblings such as design_list_water_presets, design_list_atmosphere_presets, or design_list_particle_presets, even though the category enum (water, fog, haze, celestial) visibly overlaps their domains — an explicit scoping note would have earned a 5.
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?
'Optionally filtered by category' implies how to narrow results, but there is no statement of when to call this versus the overlapping preset lists, and no guidance on whether to enumerate all 114 or filter. Usage is inferable but not directed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.