Update asset

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

With no annotations provided, the description carries the full burden and does well: it discloses the immutable GLB file and the review-queue behavior where a proposal awaits human approval while the live version keeps serving. It stops short of covering auth requirements, error conditions, or success/return semantics, but the key side effects of this mutation tool are transparent.

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?

Three sentences with zero filler, front-loaded with the core purpose, followed by the hard constraint, then the published-asset caveat. Each sentence earns its place and the structure builds logically from action to boundary to side-effect.

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?

For an 8-parameter mutation tool with no annotations and no output schema, the description covers the most important behavioral contract (immutable GLB, review queue for published assets) but leaves gaps: it gives no guidance on required slug identification, no parameter context, and no success/error semantics. Adequate for core use, incomplete for edge cases.

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 25% (2 of 8 params: aiModel and category), so the description must compensate, but it adds no parameter-level meaning whatsoever. It never explains that slug identifies the asset to edit, nor the semantics of tags, title, summary, or description. The behavioral notes are useful but do not clarify any individual parameter.

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 first sentence names a specific verb+resource ('Edit the metadata of one of the user's own assets'), which clearly distinguishes it from read tools (get_asset, my_assets) and creation/upload tools (submit_asset_from_url, finalize_upload). The GLB-immutability sentence further sharpens the boundary between metadata editing and file replacement.

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 gives clear context for when the tool applies (editing one's own assets' metadata) and an explicit exclusion ('The uploaded GLB can never be changed'), plus a critical caveat that editing a published asset does not change the live version. However, it names no alternative tool explicitly, so the when-to-use-vs-when-not guidance is implied rather than stated.

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