get_study_results

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

Annotations already cover the safety profile (readOnly, openWorld, non-destructive). The description adds genuinely useful non-schema context: the responses come from incentivised Pebbler app participants and may be incomplete, plus a cost note. It stops short of describing refresh/freshness or rate behavior.

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?

Two short sentences with no filler; the core action is front-loaded and the data-quality caveat follows. Every clause carries information.

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 should convey more about the response shape, but 'aggregate image preference votes' plus the incompleteness caveat only partially does so. No pagination, size, or structure hints are given, though the tool itself is simple.

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 carries the burden, and it says nothing about study_id. However, the single required UUID parameter is self-evident from its name and format, so the omission is low-risk. Baseline 3.

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 resource ('Retrieve aggregate image preference votes'), which is clearly distinct from sibling tools like create_study, quote_study, or get_study_status. It does not explicitly name an alternative, but the resource is unambiguous.

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 notes the data is 'Free and included in purchase,' which hints at cost/eligibility context, but it gives no guidance on when to call this versus get_study_status or get_catalog, and no prerequisites (e.g., whether the study must be purchased first).

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