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level_design_catalog

Ingest your prop catalog: footprint, height, pivot and category computed from each GLB. Returns a catalogId for place. Price: $0.50 USDC via x402, charged only on success. Part of Level design: Level dressing for 3D games.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetsYes
upAxisNoy

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does a genuinely good job on the cost dimension, disclosing that it costs $0.50 USDC via x402 and is charged only on success. It also discloses that metrics are computed automatically. It omits other behavioral traits like idempotency, partial-failure handling, and the 300-asset cap, which keeps it out of the top band.

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

Conciseness4/5

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

Three tight, front-loaded sentences move from action, to output, to price, to parent context. The trailing 'Part of Level design: Level dressing for 3D games' is mild boilerplate filler, but nothing is bloated.

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?

With no output schema, the description does supply the key return value (catalogId) and the computed fields. For a paid ingest tool with two parameters, an agent has enough to call it correctly, though more on batch limits and the upAxis/bounds fallbacks would complete the picture.

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?

Top-level schema coverage is reported at 0% (neither 'assets' nor 'upAxis' has a schema description), so the description should compensate. It does partially, listing the computed quantities and mentioning the GLB source, but it never explains the ambiguous 'upAxis' parameter or the glb / glbUrl / bounds precedence, leaving real parameter gaps.

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 names a specific verb and resource ('Ingest your prop catalog') and details the derived outputs (footprint, height, pivot, category computed from each GLB). It even ties the output to a sibling workflow ('Returns a catalogId for place'), which lets an agent distinguish it from level_design_place/revise without opening the schemas.

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?

Usage is implied rather than stated: 'Returns a catalogId for place' signals this is a prerequisite step to level_design_place, and 'Ingest your prop catalog' suggests a setup-time call. But there is no explicit when-to-use vs. alternatives guidance, no mention of re-ingesting/updating, and no exclusions against the sibling tools.

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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