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

Beyond the annotation (readOnlyHint: false), the description discloses crucial behavioral details: async rendering with polling via get_video_status, billing per second of source clip, and cost implications of 60 fps (double cost). It also specifies that 1.5x scale is allowed and batch limits. This is rich context that aids the agent in managing expectations and costs.

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 dense but every sentence earns its place: purpose, scale options, fps/cost note, model list, batch input format, accepted ID types, async behavior, and billing. It is front-loaded with the primary function and structured logically, with no redundant or filler content.

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?

The tool is complex (5 parameters, async, multiple input forms, billing) and the description covers all key aspects: input sources, batch limits, async polling, cost implications, and model families. No output schema exists, but the description points to get_video_status for status/results, making the workflow clear. It is complete for an agent to select and invoke the tool 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 coverage is 100%, setting a baseline of 3. The description adds value beyond the schema by explaining accepted input forms (Switch job ID, download_url/view_url, public https URL), batching up to 10 clips via videos, and cost nuances (60 fps doubles cost). This enhances the agent's ability to construct correct calls.

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+resource: 'Upscale and enhance one of YOUR videos (or a public https clip) with Topaz.' It clearly states the tool's function and distinguishes it from siblings like generate_video or lip_sync_video by focusing on enhancement of existing video content. The scope is well-defined.

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 provides clear context: it is for upscaling/enhancing existing videos, with batch capabilities and accepted input sources (Switch job ID, URLs). It implies usage for video enhancement rather than generation. However, it does not explicitly name alternative tools or state when not to use this tool, though the purpose is unambiguous.

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