vision_analyze_video

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

No annotations are provided, so the description must fully disclose behavior. It mentions server-side processing and local file size limits but fails to describe the return value format, error handling, authentication, or rate limits, leaving significant gaps.

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 extremely concise, using two sentences to convey the core purpose, process, and recommendations. Every sentence provides essential information without redundancy.

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 complexity of video analysis, missing annotations, and no output schema, the description should cover return values, error states, and limitations. It only partially addresses input handling and omits output and behavioral details, making it incomplete.

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 100% schema description coverage, baseline is 3. The description adds value by recommending http(s) URLs and explaining that local files are base64-encoded with size limits, going beyond the schema's parameter descriptions.

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 tool performs video understanding by sending video to a cloud multimodal model. It specifies that frame extraction and temporal alignment are handled server-side, distinguishing it from sibling tools like vision_analyze_image which targets images.

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 recommends using http(s) URLs and notes that local files are base64-encoded with size limits. However, it does not explicitly state when to use this tool versus alternatives (e.g., vision_analyze_image) or when not to use it, providing only partial usage guidance.

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