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

With no annotations, the description carries the burden and does well: it discloses output ordering (descending contrast), the recommendation marker, and AA/AAA verdicts. It does not explicitly say the tool is a pure/read-only computation, but nothing implies mutation, so the disclosure is largely adequate.

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?

A single front-loaded sentence that delivers purpose, output composition, ordering, and annotation semantics with no wasted text.

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?

No output schema exists, so the description must describe return values, and it does: candidate composition, sort order, recommended flag, and AA/AAA judgments. The optional limit parameter's effect on returns is left implicit, a minor gap.

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 documented. The description reinforces that background is the input color but adds no syntax or format detail 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?

States a specific input (a background color) and a concrete output (readable text-color candidates), and enumerates what those candidates are (light/dark versions of the same hue plus black/white references). This distinguishes it clearly from siblings like check_contrast and suggest_palette.

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 purpose strongly implies the use case (choosing readable text over a known background), but there is no explicit when-to-use versus check_contrast or suggest_palette, and no stated prerequisites. Usage is implied rather than directed.

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