video_overview_create

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

With no annotations provided, the description carries full burden for behavioral disclosure. It reveals the user approval requirement (confirm parameter), which is valuable behavioral context. However, it doesn't disclose other important traits like whether this is a long-running operation, what resources it consumes, error conditions, or what the output contains beyond what the output schema might provide.

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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence serves a purpose, though the formatting with 'Args:' and bullet-like parameter explanations could be more integrated. The information is front-loaded with the core purpose and critical requirement.

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?

Given the tool's complexity (7 parameters, creation operation) with no annotations but an output schema present, the description provides good coverage. It explains the purpose, usage constraint, and parameter meanings. The output schema existence means return values don't need description, making this reasonably complete for agent understanding.

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?

With 0% schema description coverage for 7 parameters, the description must compensate. It provides meaningful context for all parameters: notebook_id (Notebook UUID), source_ids (Source IDs with default behavior), format (explainer|brief options), visual_style (9 specific style options), language (BCP-47 code with examples), focus_prompt (Optional focus text), and confirm (Must be True after user approval). This adds substantial semantic value beyond the bare 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?

The description clearly states the specific action ('Generate video overview') and resource type (video overviews), distinguishing it from sibling tools like audio_overview_create, slide_deck_create, or infographic_create. It specifies this creates video content rather than other media formats.

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 with 'Requires confirm=True after user approval' and reiterates this in the confirm parameter documentation. This clearly indicates when the tool should be used (only after obtaining user consent) and establishes a prerequisite condition for proper invocation.

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