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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it delivers: 'Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects.' It also discloses per-mode behavior (paint darkens like real pigment, lab averages chroma toward the centroid). This fully compensates for the missing annotations.

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 long — three substantial paragraphs — but nearly every sentence earns its place given the tool's real complexity (five blend models, four color input formats, weights, safety disclosure, sibling routing). It is front-loaded with the core action and scope, with mode semantics and routing following naturally. Slightly verbose in the comparative example, but not padded.

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 high-complexity tool with 0% schema coverage and no annotations, the description is complete: it covers input formats, all mode behaviors with defaults, weight semantics, determinism/safety, and sibling alternatives. An output schema exists, so the brief 'Returns hex and rgb' is sufficient — return-value detail is not required from the description.

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 0%, so the description must carry all parameter meaning, and it does comprehensively: colors are explained with concrete examples (hex, CSS name, RNV brand name, saved-palette reference including the ':2' swatch syntax); weights are described as optional integers defaulting to equal; mode enumerates all five values (rgb/hsv/lab/paint/ryb/cmy) with semantics for each. Nothing about the parameters is left to schema inference.

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 opens with a specific verb and resource: 'Blend up to 12 colors into one.' It also explicitly differentiates from siblings by name — 'to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference' — so an agent can tell this apart from every sibling without opening schemas.

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 gives explicit when-to-use guidance with named alternatives: 'Reach for paint when BLENDING brand colors into a new one, and lab when SAMPLING between them,' and closes with the exact sibling routing for convert_color and color_difference. It even explains why paint vs lab matters for brand-color workflows with a concrete example (#00b0a0).

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