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glb_optimizer_inspect

Report on a GLB without changing it, with concrete suggestions. Price: $0.05 USDC via x402, charged only on success. Part of GLB optimizer: Make a GLB small and fast for the web or mobile: dedup, instance, join, weld, simplify, resize and re-encode textures, meshopt or draco compression.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glbNo
glbUrlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose useful traits: it is read-only, costs $0.05 USDC via x402, and is charged only on success. It stops short of explaining how the x402 payment is authorized or what the report actually contains, so key behavioral mechanics remain unstated.

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

Conciseness3/5

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

The core purpose and pricing are front-loaded and useful, but the trailing sentence describing the whole GLB optimizer family (dedup, instance, join, weld, simplify, etc.) is largely irrelevant to an inspect call and pads the definition.

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

Completeness3/5

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

With no annotations, no output schema, and 0% parameter coverage, the description is the only source of truth. It covers purpose, read-only nature, and pricing, but leaves the parameter distinction, report contents, and payment mechanics unaddressed, so it is only partially complete for a paid 2-param tool.

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

Parameters2/5

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

Schema description coverage is 0% and the description never mentions either parameter. It gives no clue that glb (inline data) and glbUrl (a URI) are alternative input forms, so an agent cannot confidently choose between them from the definition alone.

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?

States a specific verb+resource ("Report on a GLB") and adds a meaningful qualifier ("without changing it") that implicitly contrasts it with the mutating optimize siblings. It does not name glb_optimizer_optimize directly, but an agent can infer this is the read-only inspection counterpart.

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 "without changing it" implies you should call this when you only want analysis and not modification, and the sibling list supplies the alternative. However, it never explicitly states when to use this vs glb_optimizer_optimize or glb_optimizer_optimize_large, leaving the routing to inference.

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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