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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: no AI calls are made, the brief is read against Tangent's taxonomy and synonyms, result count is capped at 10, and `interpreted_as` reveals how the brief was parsed. It does not discuss latency or failure behavior for an unmatched brief, which is the main remaining gap.

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 what/mechanism/when ordering is front-loaded and each sentence carries information; the trailing example is genuinely illustrative. It is slightly dense in the first sentence, which packs the result shape, the default cap and the `why` semantics into one run-on.

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 read-only, brief-driven lookup with a full output schema, the description covers purpose, mechanism, trigger, result fields and an example. Combined with annotations that cover the safety profile, nothing an agent needs in order to invoke 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 description coverage is 100%, so the schema already documents brief, limit and platform in detail; the description's restatement of 'default 8, at most 10' is redundant with the schema. It does add a small amount via the worked example showing how brief and platform are combined, but that is marginal, so the 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?

The description gives a concrete verb and output ('Turns a design brief into a short list of references') and explains the shape of each result (a `why` explaining the shared pattern/style/category). It is clear what the tool produces, but sibling tools like search_resources or related_resources are never named, so the agent must infer the distinction from the mechanism rather than an explicit statement.

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?

It gives an explicit trigger: 'Use it when someone describes a screen or product they are about to design,' and notes the combination of taxonomy matching plus search. There is no statement of when NOT to use it or which sibling to pick instead (e.g. keyword search via search_resources), so the guidance is clear but not exclusionary.

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