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mesh_decimate_quadric_simplifier

Simplify dense 3D meshes using Quadric Error Metrics, cutting polygon counts by 50-90% while preserving silhouettes, UV borders, and vertex normals.

Instructions

Simplifies dense 3D meshes using Quadric Error Metrics (QEM), reducing polycounts by 50-90% while preserving silhouettes, UV borders, and vertex normals. (0.040 USDC on Base L2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesInput parameters or JSON string payload for the tool execution
paymentSignatureNoBase L2 USDC micropayment signature or transaction hash for x402 settlement

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the algorithm (QEM), the reduction range, and what is preserved, which is useful. However, it does not mention whether the operation is destructive, whether it modifies the input or returns a new mesh, or any side effects. The pricing note (0.040 USDC) is context but not behavioral.

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 description is a single, information-dense sentence that front-loads the core function and key benefits. The pricing note is a minor addition that could be considered extraneous but does not harm clarity. No wasted words.

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?

For a mesh-processing tool with no output schema and no annotations, the description gives a good high-level overview but lacks critical operational details: input mesh format, output format, whether the operation is destructive, and how to specify reduction parameters. The sibling list shows many mesh tools, so more specificity about input/output would help an agent select and invoke it correctly.

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 description coverage is 100% for the two parameters, but the descriptions are generic ('Input parameters or JSON string payload'). The tool description does not explain what fields the payload should contain (e.g., mesh format, target polycount, preserve borders). With 100% coverage, baseline is 3, and the description adds no specific parameter guidance.

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 description clearly states the tool simplifies dense 3D meshes using Quadric Error Metrics, with specific outcomes (reducing polycounts by 50-90%, preserving silhouettes, UV borders, and vertex normals). This distinguishes it from siblings like optimize_3d_mesh, mesh_subdivision_loop_surface, and mesh_watertight_manifold_auditor.

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 description implies usage for dense meshes needing polycount reduction, but does not explicitly state when to use this tool versus alternatives like optimize_3d_mesh or gltf_draco_mesh_quantizer. It mentions preservation of UV borders and normals, which hints at suitability for textured models, but no explicit exclusions or alternative routing.

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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