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

Goes beyond the readOnlyHint annotation by declaring 'no cost' and describing the exact return payload (a recommended look name with a reason and alternatives). It also discloses the input-dependent behavioral difference (image prompt included only when image_id is passed), which the annotations do not cover.

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 compact sentences, front-loaded with what the tool does and its cost profile, followed by the parameter conditional and the next-step handoff. No filler.

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 carries the return-format burden and does so ('look name with a reason and alternatives'), and it covers cost, the parameter conditional, and the follow-up action. Nothing an agent needs to call it correctly is missing.

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 coverage is 100%, so the baseline is 3, but the description adds real semantic value: it explains that image_id pulls the image prompt into the suggestion, while omitting it falls back to the colorist crew brief. That is a behavioral consequence of the parameter, not just a restatement.

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+resource ('suggest a grade look for a project') and immediately distinguishes itself from the sibling that performs the mutation by naming lab_grade. An agent can tell this is the advisory/read step rather than the apply step.

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?

Explicitly frames the workflow: use this to get a recommendation, then 'apply it with lab_grade(look: …) once the user agrees.' It also states the branching condition (with image_id vs. without) that selects different behavior, leaving nothing to inference.

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