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

Annotations already establish a safe, idempotent read, and the description adds real behavioral context beyond that: default vs. opt-in listing scope and the rule that opt-in models run only on explicit user request. With no output schema, it also describes the return shape (id, media type, tier, price in Gems, summary; variants with model_id, options, image budget, trade-offs), which is valuable. Minor gaps only, such as ordering or result size.

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?

Purpose and defaults are front-loaded, but the body is a dense run-on paragraph with stacked parentheticals like '(`defaults`)' and interleaved field enumerations that make it harder to parse than needed. Little is outright wasteful, but the structure could be far cleaner.

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?

Covers what is listed, what is excluded by default, how to include opt-ins, the default model per media type, and the required follow-up call to get_model. For a two-optional-parameter read tool with no output schema, nothing an agent needs is missing.

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 baseline is 3, but the description goes further by explaining the consequence of include_opt_in ('the rest are opt-in... run only when the user asks for one by name') rather than just restating the flag. The type filter's semantics are covered by the schema's enum and its constraint, so the description adds little there.

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 ('List the models Mage generates with') plus the intent behind it (guiding model choice). It also distinguishes itself from the sibling get_model by explicitly deferring detailed single-model lookup to that tool.

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 concrete defaults per media type (mango-v3 for images, cherry-2-pro for video, seed-audio-1.0 for audio) and the condition under which they apply ('Unless the user names a model'). It also explains that opt-in models are only listed with include_opt_in and only run when a user names one, and directs the agent to call get_model before generating.

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