suggest_categories

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

Annotations already establish readOnlyHint=true, so the safety profile is covered. The description adds a non-obvious operational trait — that this call does not consume search tokens — which is exactly the kind of cost/quota context annotations cannot express. It omits pagination/ordering behavior, but that is minor here.

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 tight sentences, front-loaded with the core resolution behavior, followed by the integration instruction and the quota note. No filler or redundancy.

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 usefully implies the return shape (items carrying a uri such as news/Business) and how to consume it downstream, which is the most important thing an agent needs. Minor gaps remain around ordering/pagination and the relationship to sibling suggest tools.

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% (page, count, and prefix all documented in-schema), so the baseline is 3. The description adds no format or constraint detail about prefix, page, or count beyond the schema, nor does it clarify the default paging semantics.

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 and transformation: resolve a topic name into category URIs, with two concrete example outputs. It stops short of differentiating itself from the near-identical siblings suggest_concepts / suggest_sources / suggest_locations, so the agent must infer that this one is specifically for category URIs.

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 a downstream workflow hint (pass the returned uri as category_uris to search_articles / search_events), which is genuinely useful. However it never says when to choose this tool over the sibling suggest_* tools or what input shape is expected beyond the schema's prefix description, so usage is implied rather than stated.

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