analyze_video

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

With no annotations, the description carries the full burden for behavioral transparency. It discloses practical constraints: 'Maximum file size: 8MB' and 'Supports MP4, MOV, M4V formats,' which are valuable. However, it does not describe the output format, failure modes, or any asynchronous behavior, leaving some uncertainty about what the tool actually returns.

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: a one-sentence summary, a concise bulleted list of use cases, and a final sentence with constraints. It is front-loaded with the primary purpose, and every line contributes meaningful information without unnecessary verbosity.

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 relatively simple tool with only two parameters and no output schema, the description covers the essential context: what it does, when to use it, and practical limits. The main gap is the lack of explicit output behavior, but the use cases imply textual descriptions, so it is reasonably complete.

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 input schema already has 100% description coverage, with both 'video_source' and 'prompt' adequately described. The tool description adds no additional semantic meaning beyond what the schema provides (e.g., it repeats format support but does not clarify prompt syntax or expected detail level), so the baseline score of 3 is appropriate.

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's function with a specific verb and resource: 'Analyze video content using advanced AI vision models.' It further distinguishes itself from siblings (e.g., analyze_image) by focusing exclusively on video and listing concrete use cases like 'Extract key moments' and 'Identify objects, people, or activities in video'.

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 when-to-use guidance through the bulleted 'Use this tool when the user wants to:' list, covering multiple video analysis intents. It does not, however, mention when not to use it or name alternative tools (like analyze_image for static images), leaving the exclusion criteria implicit based on the sibling context.

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