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

With no annotations supplied, the description carries the full behavioral burden, and it does disclose two useful facts: the return shape ({ processedImage }) and a concrete cost of 3 credits. It is silent on whether the rest of the image is untouched, whether the operation is synchronous, and what happens on insufficient credits, so meaningful gaps remain for an unannotated tool.

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?

Three short sentences with zero filler: purpose first, then return value, then cost. Every clause carries distinct information and the most decision-relevant facts lead.

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 simple two-parameter tool with no output schema, the description covers the essentials: what it does, what it returns, and what it costs. The absence of annotations means some operational detail (failure modes, whether the source image is modified) is left uncovered, but not enough to block a correct call.

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 both parameters are already well documented, including the semi-transparent red marking convention the app uses. The description adds only the high-level framing of 'marked area' and 'described in words', which does not meaningfully extend beyond the schema; baseline 3 applies.

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 ('Replace a marked area of an image') plus the input modality ('something described in words'), which is unambiguous about what the tool does. It does not, however, contrast itself with plausible siblings such as object_remover or ai_expand, so the agent must infer the boundary from the name alone.

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?

Usage is implied rather than stated: the agent can infer it should be called when it has an image with a marked region and a text description of the replacement. There is no explicit when-not guidance and no named alternative for the closely related removal or expansion tasks, leaving selection between siblings to inference.

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