analyze_video

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

Beyond the annotations, the description discloses that this operation spends Watch minutes, returns immediately with an analysisId, completes asynchronously, and reuses prior results if the video was analyzed before. These are essential behavioral details that the annotations do not cover.

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 compact but information-dense: it covers purpose, visual evidence value, cost, asynchronous polling, and caching in roughly five sentences. Every sentence adds meaningful guidance, and there is no redundant restatement of annotations or schema names.

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?

With no output schema, the description still tells the agent what the analysis will contain and how to coordinate with get_analysis for the final result. The async handoff, cost, and cached-result behavior make the full workflow clear and actionable.

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 documents all three parameters completely, including mode values, defaults, and the meaning of partial and video. The description does not add new parameter-specific details, though it gives helpful high-level context about the analysis result and cost behavior.

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 opens with a specific verb and resource: "Start a deep visual analysis of a YouTube video" and lists concrete outputs such as chapters, key moments, on-screen text, and timestamped evidence. It distinguishes itself from sibling tools like search_transcript and get_transcript by stressing that it reads the picture, not just captions.

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 clearly states when to use this tool: when the transcript misses visual content like slides, charts, or demos. It also explicitly tells the agent to poll get_analysis rather than waiting, and notes that previously analyzed videos return ready immediately. It does not mention at all the exact alternative transcript tools other than implicating them.

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