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

Annotations already declare read-only, idempotent, closed-world behavior. The description adds genuinely new context beyond them: the operation is free (no credit consumption) and the response includes model, default params and a prompt template with {subject} placeholders.

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?

Two tight sentences: what is listed first, how to use the output second. No filler, and the most decision-relevant content is front-loaded.

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?

With no output schema, the description adequately characterizes the returned fields and the placeholder convention. Minor gap: nothing is said about result size, ordering or whether the full preset set is returned.

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 100% and the category parameter already carries example values (camera, transition, vfx, viral, product, cover). The description's category list largely mirrors that, so it adds little beyond the schema.

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?

Specific verb ("List") plus resource ("AI Studio effect presets") with an explicit enumeration of the preset families covered. It also states the payload shape (model, default params, prompt template), which cleanly separates it from siblings like list_studio_models and list_templates.

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?

It tells the agent the downstream workflow explicitly: take the preset_id and pass it to studio_generate with a subject in prompt. That is actionable guidance, though it never states when to prefer this over list_studio_models or list_templates.

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