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

Even without annotations, the description discloses several behavioral traits: the underlying model (NAFNet), processing time (~2 min), payment model (110 sats, Bitcoin Lightning), and the need to call create_payment first. It doesn't explicitly mention async result retrieval, but it provides meaningful context beyond basic functionality.

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 concise but information-dense. It flows logically from purpose to model to usage guidance to pricing and prerequisites. Every sentence contributes value, though the density of the last two sentences about payment could be slightly restructured without losing meaning.

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 description covers the tool's purpose, limitations, pricing, and required prerequisite (create_payment). It doesn't mention the return format or potential error cases, but given the lack of output schema, these omissions are minor. Overall, it provides sufficient context for an agent to decide whether to use the tool and how to invoke it.

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%, with all parameters already well-described (including enum meanings and defaults). The tool description adds no new parameter-level information but confirms the task_type options and data URI support, which is already in the schema. Baseline 3 is appropriate.

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 uses a specific verb ('recover detail') and names the resource ('camera-shake and accidental motion blur'), and it distinguishes the tool from siblings by clarifying what it does and does not handle (e.g., not artistic motion blur). It also mentions a secondary use (denoising), which adds clarity.

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?

Explicitly states when to use ('handheld shake, bumped camera, whole-frame uniform blur') and when not ('intentional panning blur, bokeh/depth-of-field, artistic motion effects'). Also includes cost and payment requirements, giving clear context for practical use.

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