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

Beyond the annotations, the description discloses key behavior: it spends the user's coins, price depends on length/settings, high-cost calls require explicit confirmation with a token, it returns a task id for follow-up, and AI-assistant generation is charged in VerseIn coins with unlimited-plan allowances not applying. These details materially help the agent avoid unexpected charges and handle the confirmation workflow correctly.

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 front-loaded with the core action and then covers cost, confirmation, and follow-up. It is dense and mostly earns its space, though the charging point is restated slightly across sentences ('Spends the user's coins' and 'Generating through an AI assistant is charged in VerseIn coins').

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 a 10-parameter tool with 100% schema coverage and an output schema, the description supplies the behavioral context the schema cannot: cost implications, the confirmation threshold and token flow, and the need to follow up with 'get_tasks.' An agent has enough information to invoke it and handle the main edge cases correctly.

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 100%, so the schema itself already explains all 10 parameters. The description adds some workflow context around cost and confirmation tokens, but it does not add parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate when the schema carries full parameter documentation.

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 states a specific verb and resource: 'Upscale a video ... to a higher resolution or frame rate,' and identifies the input as 'a VerseIn media URL.' This is clear enough to distinguish it from image upscaling by resource and from edit/reframe/extend by purpose, though it does not explicitly name sibling alternatives.

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?

It gives clear operational context: the call spends coins, priced by video length and settings, and calls over the confirmation threshold return 'needs_confirmation'; the agent should ask the user and retry with the token. It also directs the agent to follow the returned task id with 'get_tasks.' It does not state when to choose this over editing, reframing, or extending a video, so it stops short of full alternative routing.

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