分析视频

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

Annotations already declare readOnlyHint and openWorldHint. The description adds that it works with local paths and HTTP(S) URLs and allows specifying frame count and profile, but does not disclose output structure or any limitations. Beyond annotations, it adds moderate context, so a 3 is appropriate.

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 a single, compact sentence that clearly conveys the core function and key optional parameters. No unnecessary words or 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?

The tool has good parameter documentation and a read-only annotation. The description covers the essence of the operation and its main options, but lacks explicit guidance on model profile selection or relation to sibling tools. It is adequate but not exhaustive, so a 4 is appropriate.

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%, with each parameter already described. The description only paraphrases 'frames' and 'profile' without adding new semantic detail, so it does not exceed the schema baseline.

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 explicitly states the tool extracts frames from local or HTTP(S) videos and performs structured understanding, with configurable frame count and model profile. This clearly distinguishes it from sibling tools analyze_image (images) and list_vision_models (model listing).

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 implies usage for video analysis but does not explicitly mention when to use it over analyze_image or how to utilize list_vision_models for profile selection. No exclusions or alternatives are stated, so guidance is implied rather than explicit.

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