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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds valuable context beyond that: it states the tool is 'FREE', returns url+label, and includes the side effect that passing brandId 'switches this key's active brand like use_brand'. This discloses internal state change and cost implications, which are not covered by annotations. It does not contradict the read-only hint because changing the active brand is not a destructive data modification. The description adds meaningful behavioral context.

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 bit lengthy but every sentence carries useful information: the scope, the free nature, the return format, the usage recommendation, and the brandId behavior. It is front-loaded with the main purpose and then details, so the structure is effective. It could be tightened slightly, but it is not verbose or repetitive, making it highly efficient.

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 tool with one optional parameter, no output schema, and simple return value (url+label), the description is complete. It explains what the tool returns, the scope of photos, the side effect of brandId, and when to use it. An agent has everything needed to call it correctly and interpret results. There are no missing pieces.

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?

The input schema has 100% coverage for the single parameter brandId with a clear description. The tool description goes beyond the schema by explaining the side effect of passing brandId ('switches this key's active brand') and clarifies that omitting it uses the active brand. This adds meaning beyond what the schema provides, justifying a score above the baseline of 3.

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 lists product photos already saved in the workspace, includes the brand's product library and app-store screens, and even mentions that photos from other creations are surfaced. It distinguishes the tool from set_product_image by explicitly saying to call it before that tool, and the term 'product photos' is specific enough to differentiate from list_library or other list tools. The verb 'List' plus resource 'product photos' is precise and unambiguous.

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 provides explicit usage guidance: 'Call it before set_product_image to see the existing photos you can reuse.' This gives a clear context and workflow. It also explains the brandId parameter behavior and its side effect of switching the active brand, which helps an agent decide whether to pass it. However, it does not explicitly mention when not to use this tool or alternatives like list_library, so it is slightly less complete than a perfect score.

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