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

Beyond the annotations, the description discloses meaningful behavior: paginated structured output with source_class, provenance, snapshot, pagination and limits; no inference/aggregation; snapshot-limited coverage; empty data array on no match; and argument errors for missing/invalid input. This is strong behavioral disclosure, especially with no output schema present.

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 compact, front-loaded with the primary purpose, and every remaining sentence adds operational value: return shape, no-inference behavior, coverage limits, empty-result behavior, and error conditions. There is no filler or unnecessary elaboration.

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?

Given the tool's moderate complexity and no output schema, the description covers the essential operational details: required inputs, optional filtering, paginated results, result field categories, empty results, error handling, and snapshot scoping. An agent has enough information to call the tool correctly and interpret the response shape.

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 already explains every parameter, including exact-match and substring-match semantics. The description adds only a high-level mention of 'country' and 'institution' inputs and that country is required, which is redundant with the schema. Therefore baseline 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?

The description states a specific action ('Find'), a concrete resource ('recorded institutions and roles for a country'), and an optional filter ('institution text'). It also clarifies the tool's scope as a read-only query over recorded facts, which distinguishes it from aggregation or inference tools among the siblings.

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 gives clear context: use it to retrieve recorded country-institution facts with optional institution filtering, and it notes that no new inference or aggregation is performed. It does not explicitly name alternatives or state when not to use it, but the usage context is unambiguous enough for an agent to select it appropriately.

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