research_query

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only states that the tool queries with filters; it doesn't disclose whether the operation is read-only, how pagination works, whether authentication is required, or how filter parameters interact.

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 a single, front-loaded sentence with no filler. It is appropriately concise, though the brevity borders on under-specification for a tool of this complexity.

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 7 parameters, no annotations, and overlapping sibling tools, the one-sentence description is insufficient. An output schema exists, but the description fails to cover parameter semantics, usage context, or behavioral traits, making it incomplete for safe invocation.

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%, and the description adds no meaning to the 7 parameters. 'With filters' is generic and does not explain mode, limit, model, since, until, offset, or category, leaving the agent without essential parameter 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?

The description clearly identifies a query operation against a 'published research corpus' with filtering, which is a specific verb+resource pairing. It distinguishes itself from sibling research_info and research_stats by the query/with-filters emphasis, though it doesn't explicitly name alternatives.

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 provides no guidance on when to use this tool versus siblings like research_info, research_stats, or dataset_stats. There are no prerequisites, exclusions, or alternative tool mentions; the only signal is the implied filtering use case.

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