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

Annotations already establish a safe, closed-world read (readOnlyHint=true, openWorldHint=false). The description adds real behavioral content beyond that: it discloses the mapping algorithm (CSS Color 4 gamut mapping in OKLCH) and the preservation guarantees of the fallback (lightness and hue kept), which tells the agent what to expect from results.

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 dense sentence that front-loads the primary operation (gamut check across three spaces) and appends the fallback behavior. No filler or repetition.

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?

With no output schema, the description must carry return-value meaning, and it does describe both outputs: per-gamut fit and a lightness/hue-preserving sRGB fallback. It stops short of specifying the exact result shape (e.g., booleans per gamut), which is a minor gap for a simple one-parameter tool.

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?

Only one parameter, and schema description coverage is 100% — the schema already enumerates accepted formats (#ff5733, rgb(), hsl(), oklch(), names, Tailwind classes) in detail. The description adds no parameter-level information beyond that, so 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 verb (check) and resource (color gamut fit across sRGB, Display P3, Rec. 2020) and adds the secondary output (closest sRGB fallback). This clearly separates it from siblings like check_contrast and convert_color, which do different color checks.

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 implies when to use it — when you need to know if a color is out of gamut and want a printable/displayable fallback — but it never names alternatives or states exclusions (e.g., 'use convert_color to change color space'). Usage is inferable rather than guided.

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