analyze_video

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

With no annotations, the description discloses platform-specific processing modes (direct vs. background) and return of job_id. Does not cover rate limits or auth, but the core behavior is transparent.

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?

Concise, well-structured, and front-loaded. Every sentence adds essential information without 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?

Given the presence of an output schema, the description appropriately omits return value details. It covers platform differences and references the polling tool, making the overall usage clear.

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%. Description adds value by explaining how the url parameter affects processing flow (direct vs. background), which goes beyond the schema description. Prompt and model defaults are noted.

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 from YouTube, TikTok, or Instagram with comprehensive audio+visual analysis. It differentiates behavior per platform and distinguishes from sibling tools like check_analysis_job.

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?

Provides clear context on when to use (analyze a video) and mentions the polling mechanism for non-YouTube videos via check_analysis_job. Does not explicitly state exclusions or when not to use.

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