vision_video

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

Since no annotations are provided, the description carries the full burden. It discloses key behaviors: default model configuration, optional reasoning chain support, and limits on response length. It also notes that thinking is ignored by providers that don't support it. No contradictions with annotations.

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 well-structured with a clear header, parameter descriptions, and return value note. It is concise but provides necessary details. A slight reduction from 5 because the parameter explanations could be more terse without losing clarity.

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 (5 parameters, 2 required) and the presence of an output schema, the description is largely complete. It explains all parameters, usage tips, and return type. It could briefly mention what happens with the 'thinking' parameter for models that do support it.

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?

The description adds significant meaning beyond the input schema. It explains that 'videos' can be URLs, local file paths, or data URIs; clarifies what 'prompt' should contain with temporal examples; specifies optional model override and response length cap; and details the 'thinking' parameter's compatibility. This is particularly valuable given the 0% schema coverage.

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 it understands one or more videos with a vision model, which is a specific verb+resource combination. It also distinguishes itself from sibling tools like vision_analyze (likely for images/analysis) and vision_ocr (text extraction) by explicitly focusing on videos and temporal questions.

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 guidance on when to use this tool (understanding videos) and includes tips like 'for temporal questions be explicit about time points.' However, it does not explicitly mention when NOT to use it or direct the agent to alternative sibling tools for non-video use cases.

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