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

Annotations already cover the read-only, non-destructive nature, so the description's job is lighter. It adds the useful detail that the result is 'full' and includes captions, frames, and transcript, but it does not disclose response size, error behavior, or media-type constraints. This is adequate given the existing annotation coverage.

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?

A single, compact sentence with no redundant wording. The essential content of the tool is front-loaded, and the parenthetical adds precise value without bloating the definition.

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 read-only, single-parameter lookup with annotations covering safety and no output schema, the description provides enough to select and invoke the tool correctly: what media_id targets and what the return includes. Nothing critical is missing for an agent to act.

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%: the only parameter, media_id, is described as 'Document ID' in the schema. The tool description does not add extra meaning about the format or origin of media_id, so it stays at the baseline for fully covered schemas.

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 a specific verb ('Get'), a resource ('media description'), and the scope ('full AI-generated description for an image or video') with a concrete content breakdown (captions, frames, transcript). This distinguishes it from siblings like get_relevant_frames or semantic_search_media, which serve different retrieval purposes.

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?

Usage is implied: when you have a media_id and want the stored full description, this is the tool. However, there are no explicit statements about when not to use it or which sibling to prefer in overlapping scenarios, such as get_relevant_frames for frames alone.

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