List every filter value search_library accepts

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

Beyond the annotations, the description adds valuable behavioral context: it costs no API call and no quota, and incorrect category names are rejected rather than ignored. It also discloses that the tool reports what the Google Photos API cannot do, setting accurate expectations.

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 compact and front-loaded with the core purpose, then adds a short, high-value usage warning. Every sentence earns its place and no irrelevant details are included.

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 simple introspection tool with one optional parameter and strong annotations, the description fully covers what the tool returns, when to use it, and its cost/quota behavior. No output schema is needed because the return value is the list of accepted filters itself.

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 100%, so the one optional parameter is already fully documented in the input schema. The description adds no parameter-specific meaning, which matches the baseline of 3 for high schema coverage.

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 names a specific verb (Return) and a precise resource (the filter values search_library accepts), and further narrows it to content categories, media types, and feature filters. It also distinguishes the tool from search_library by making clear it lists accepted values rather than performing searches.

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 clearly tells the agent when to call it: 'Read this before guessing a category name.' It also notes that a wrong guess is rejected, reinforcing the need to consult this tool first. It does not explicitly mention alternatives, but none are needed for an introspection tool.

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