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

With no annotations at all, the description carries the full burden; it does useful work by disclosing the credit cost (2 credits) and the return shape ({ processedImage }). It does not cover failure modes, whether the source image is stored, or any rate/permission constraints, so meaningful behavior remains undisclosed for a paid mutation.

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?

Two short sentences, zero filler. The core operation is front-loaded, followed by the return value and cost — every sentence earns its place.

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 3-parameter tool with 100% schema coverage, the description covers operation, return key, and cost, which is nearly everything an agent needs. Only edge behavior (URL fetch failures, output size) is left out, and there is no output schema requiring explanation.

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% and the schema already defines all three parameters, including the enum values and the 'base64 data URI or HTTPS URL' formats. The description adds no meaning beyond that — the content/style distinction is already spelled out in the schema properties.

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 gives a specific verb and resource ('Repaint a content image') and disambiguates the two image roles — content vs. style reference — so an agent can tell it apart from single-image styling siblings like cartoonize or ai_filters. It stops short of naming any sibling or contrasting behavior explicitly.

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 by the image role split: you need one photo to restyle plus one style source, which naturally separates it from one-image transform tools. There is no explicit when-to-use/when-not or named alternative, so the agent must infer selection criteria.

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