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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description goes beyond that by disclosing credit cost ('1 credit per record returned, minimum 2'), which is a materially useful behavioral trait for invocation, though it omits any note on suppression/return volume (partly covered by the output schema).

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 sentences, zero waste, front-loaded with purpose and grain, then cost, then alternative routing. Each sentence earns its place and covers a distinct concern.

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 9 params (all schema-documented), annotations present, and an output schema handling return values, the description supplies exactly what is missing: aggregate grain, cost, and sibling routing. Nothing needed to call the tool correctly is absent.

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 baseline is 3. The description adds meaning beyond the schema by tying page_size directly to credit cost ('keep page_size to what you need'), giving the agent a reason to size the request correctly rather than just a valid range.

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 (search) and resource (aggregate Product Hunt launch trends by category and time period), and immediately clarifies the row grain ('category-over-time rollup, not a product or maker record'). This lets an agent distinguish it from the entity-level siblings without opening any schema.

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 names the alternatives (datasets_producthunt_products_search, datasets_producthunt_makers_search) and the condition that selects them ('for entity-level data'), routing the agent away from this aggregate tool. Also adds a cost-based usage constraint on page_size.

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