Ytdlp Plan Download

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

Annotations (readOnlyHint, idempotentHint, destructiveHint=false) indicate safe, read-only behavior. The description confirms no files are written and provides additional behavioral details like returning exact argv and risk analysis, adding value beyond annotations.

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 a single, front-loaded sentence that efficiently conveys the tool's purpose. It is concise, but a slight restructuring (e.g., bullet points for the list of answers) could improve readability.

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 tool has 13 parameters and a complex nested schema, the description is too short. It lacks details on parameter usage, required vs. optional, and examples. An AI agent may struggle to construct correct inputs without more guidance.

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 description coverage is 0%, and the description does not explain any of the 13 top-level parameters or their defaults. Despite the schema being self-documenting to some extent, the description should provide guidance on how to structure common parameters like 'auth' or 'kind'.

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 performs a dry-run of downloads without writing files, and lists specific outcomes (format resolution, dependencies, risks, argv). It distinguishes itself from sibling download tools by emphasizing the dry-run nature.

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 explains when to use the tool ('to answer what would happen, which format best quality resolves to...'). It does not explicitly mention when not to use or compare with other plan tools like ytdlp_plan_postprocess, but the context is clear enough.

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