Check whether an asset is game-ready

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to re-state safety. It adds valuable behavioral detail: errors fail the asset, warnings do not; every threshold is overridable (implying parameter customization). The note that it is free and fully local adds context about execution environment. This goes beyond what annotations provide, though it could be more explicit about output structure or error handling.

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?

The description is a single dense paragraph but is well-ordered: starts with 'FREE and fully local', then describes the core function, then error/warning behavior, then overridability, then the pairing workflow. Every sentence carries information and nothing is redundant. It could be broken into bullet points for scannability, but it's efficient and not bloated. Slight deduction for length; it could be shortened without losing content.

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?

The description explains the output (pass/fail with per-check reasons) and the checks, but it omits critical usage details: it does not state that one of modelPath or assetJobId must be provided (both are optional in schema), nor does it mention default thresholds or units (e.g., triangle count, texture size). Without an output schema, the return format is only vaguely described. The pairing with normalize_mesh is helpful, but the description lacks completeness for an agent to call correctly without additional inference.

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 only 17% (only modelPath and assetJobId have descriptions). The description lists the checks performed (UVs, normals, tangents, triangle budget, etc.) but does not explicitly map each check to its corresponding parameter (e.g., requireUVs, maxTriangles). The statement 'Every threshold is overridable' implies parameters exist but doesn't clarify their semantics. Given the low schema coverage, the description should compensate more by naming parameters or specifying units. It adds some value by listing the checks, but an agent might still be unsure how to set specific thresholds.

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?

The description clearly states the tool judges glTF/GLB assets against a shipping policy and returns a pass/fail verdict with per-check reasons. It lists specific checks (UVs, normals, tangents, triangle budget, etc.) and distinguishes itself from normalize_mesh by describing the pairing workflow. This is a specific, actionable purpose that an agent can easily understand without opening the schema.

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?

The description explicitly notes it is free and fully local (no network/credits), which is a condition for when to use it. It also instructs to pair with normalize_mesh: run this first, normalize, then run again to verify repair. This provides clear 'when to use' context. It does not explicitly mention when not to use or list alternatives, but given the tool's role as the validation step, the guidance is sufficient. A small deduction for not stating that it's a pre-shipping check among other potential validation paths.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.