analyze_video

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

No annotations are provided, so the description carries the burden. It discloses synchronous vs. async behavior per platform, the use of Gemini AI, and that a job_id is returned for async cases. It does not cover rate limits or auth, but for a non-destructive tool this is sufficient.

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 concise (4 sentences) and well-structured, with clear separation of platform behavior. Every sentence adds value, and the async polling note is front-loaded.

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 no annotations and the presence of an output schema, the description covers purpose, usage, and async behavior. It misses potential rate limits or authentication constraints, but provides enough context for correct invocation.

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%, so the description adds value beyond the schema. It provides the full default prompt which gives agents a clear understanding of analysis depth, and explains the model parameter default. This adds meaningful context beyond the schema 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 analyzes videos and photo/slideshow posts from YouTube, TikTok, and Instagram. It distinguishes itself from sibling tools like analyze_video_segment and ask_about_video by focusing on comprehensive audio+visual analysis.

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 explicitly explains when to use this tool (for full analysis) and when to use alternatives (e.g., check_analysis_job for polling async results). It also notes platform-specific behavior (YouTube synchronous, TikTok/Instagram async).

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