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

Annotations only say readOnlyHint=false / destructiveHint=false, so the description carries real added weight: it discloses credit cost per view, that the cost query is free with no charge, that missing images are refunded, and the dependency that side/back/top/detail edit the front anchor. Those are exactly the side effects and constraints an agent needs before spending a user's credits.

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 dense sentences, front-loaded with purpose then cost then required workflow. Nothing is padded — each sentence delivers either scope, pricing behavior, or a mandatory pre-call step.

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 a credit-spending generation tool with no output schema and a mutation flag, the description covers cost, refunds, the confirmation gate, and the view dependency chain. It still leaves unclear what the call returns (asset/image references) and does not explain the 'anker' flag, keeping it just under complete.

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 coverage is only 20%, so the description must compensate, and it partly does: it explains that 'front' is text-to-image while the other view values edit the front anchor, and it restates get_cost as a free price query. However, the 'anker' boolean and the prop_id/project_id parameters get no semantic explanation anywhere, so the compensation is incomplete.

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?

States a specific verb and resource — 'Generate product-photo views of a prop' — plus the underlying model (Flux 2 Pro), which distinguishes it from the generic lab_generate or the character-reference generator. It does not explicitly name a sibling it could be confused with, so it stops just short of a 5.

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?

Gives a concrete operating protocol: call first with get_cost:true, quote exact credits to the person, obtain confirmation before generating. That is clear when-to-use and prerequisite ordering. It does not address when to skip this tool or which sibling to pick instead, leaving a minor gap.

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