Rengi Forge

glb_optimizer_lod

Generate a LOD chain from a GLB (default 100/50/25/10% of triangles) with locked borders so UV seams and silhouettes hold; one GLB per level, a side-by-side render and Unity LODGroup transition heights. Price: $0.20 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.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "glb_optimizer_lod"
  }
}

Input Schema

Name	Required	Description
`glb`	No
`glbUrl`	No
`ratios`	No
`lockBorder`	No	Keep open edges and UV seams in place (recommended).

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 20, 2026

TDQS

A3.6/5.0

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 it does disclose meaningful behavior: pricing ($0.20 USDC via x402, charged only on success) and the exact output artifacts produced. It does not cover processing time, size limits, or failure modes, but the cost/charging semantics and output shape are strong additions.

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?

The core purpose, defaults, outputs, and price are front-loaded in two dense sentences with no wasted words. The trailing 'Part of GLB optimizer...' sentence is family marketing that repeats context already available from sibling names, adding length without adding selection value.

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 output schema or annotations, the description does a fair job explaining what is returned (per-level GLBs, render, transition heights) and the cost model. However, it omits how to provide the input GLB and any limits on ratios or mesh size, leaving a real gap for a 4-parameter tool.

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?

Schema coverage is only 25%, so the description must compensate. It explains the ratios default (100/50/25/10% of triangles) and restates the border-locking behavior, but leaves the two input fields (glb vs glbUrl) completely unexplained, so an agent cannot tell how to supply the asset.

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 first sentence states a specific verb and resource ('Generate a LOD chain from a GLB') and then enumerates the concrete outputs (one GLB per level, a side-by-side render, Unity LODGroup transition heights). This clearly distinguishes it from siblings like glb_optimizer_optimize or glb_optimizer_convert, which do not produce LOD chains.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no conditions for choosing this over glb_optimizer_optimize or glb_optimizer_optimize_large, and no stated exclusions. The only contextual signal is the family blurb ('Part of GLB optimizer'), which describes the suite rather than when this specific tool applies.

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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