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

No annotations are provided, so the description must fully disclose behavioral traits. It states the core function but omits critical details such as authentication requirements, rate limits, whether the video is downloaded or streamed, error conditions, or side effects. This leaves the agent underinformed about important operational aspects.

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 extremely concise: a one-sentence purpose followed by compact parameter and return descriptions. It front-loads the main goal and avoids any extraneous text. Every sentence earns its place, making it efficient for an AI agent to parse.

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 tool with two simple parameters and no output schema or nested objects, the description covers the core input/output. However, it lacks behavioral context (e.g., processing time, URL validation, error handling) and the return format is vaguely described as 'formatted text'. This leaves some reasonable gaps in context, making it merely adequate.

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 schema provides zero description coverage (0%), so the description compensates by explaining both parameters: 'video_url (str): The URL of video to process' and 'use_audio (bool): Whether to use audio for transcription. Should always be True.' The explanations are clear and include a usage hint, adding significant value beyond the raw schema.

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 'Extracts and formats video content into structured text, optimized for LLM processing and analysis.' This provides a specific verb (extracts) and resource (video content), and it also indicates the output format. With no sibling tools, differentiation is not required, and the purpose is unambiguous.

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 offers a clear usage constraint for the 'use_audio' parameter: 'Should always be True.' This guides the agent in correct usage. However, it does not provide explicit 'when to use' or 'when not to use' context, but given the absence of sibling tools, the implied usage (whenever video text is needed) is sufficient.

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