open_payments_research

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds that the tool 'shows research funding amounts, sponsors, and principal investigators,' which previews the response content. It does not disclose additional behavioral traits such as pagination or auto-year behavior, but that is not necessary given the annotations.

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 description is three sentences and front-loads the core purpose. The middle sentence is a useful disambiguation, and the final sentence previews output fields. Slight redundancy ('research payment data' followed by 'grants, clinical research funding') prevents a top score.

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 search tool with five optional parameters and no output schema, the description provides enough orientation: what it searches, how it differs from general payments, and what the results show. Parameter details are fully covered by the schema, and annotations cover safety. It could name the exact general-payments sibling, but this is a minor gap.

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 fully documents all five parameters. The description does not add parameter-specific semantics beyond the schema, such as format or interaction. Baseline of 3 is appropriate.

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?

Description opens with 'Search Open Payments RESEARCH payment data,' a specific verb and resource, and immediately clarifies the scope: grants and clinical research funding from pharma to doctors. It also contrasts with general payments, which helps an agent distinguish this from the broader Open Payments search tools. However, it does not name the specific sibling (e.g., open_payments_search), so differentiation is implicit rather than explicit.

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 phrase 'Separate from general payments' gives useful context that this tool should be chosen for research/grants rather than general Open Payments data. But there is no explicit when-to-use/when-not-to-use statement or named alternative. An agent must infer that open_payments_search is the general counterpart.

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