omniseek_institution_cohort

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

With no annotations, the description carries the full behavioral burden, and it delivers: it explains ranking by output at the institution in the field, the all-fields default behavior, year_from recency bias, and the lack of PhD-student verification due to OpenAlex limitations. It also discloses the exact return shape.

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 long but dense, with the primary use case front-loaded before important caveats and return details. The fully-qualified MCP name warning is useful invocation context, and no sentence is purely filler.

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 zero schema parameter descriptions and no output schema, this description is unusually complete: it covers what the tool does, when to use it, how parameters change behavior, what the result is, and its limitations. An agent has enough to invoke it correctly.

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 must compensate. It explains institution, concept, and year_from with concrete examples and consequences, though limit is left to inference from its schema default. This is a strong recovery from an otherwise bare schema.

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 opens with a clear, specific purpose: retrieving the people-roster of a lab, department, or university, optionally scoped to a field. It explicitly frames this as the "who's at this lab" question and distinguishes it from co-authorship, making the tool's identity 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?

It gives explicit when-to-use guidance, explains the field-scoping caveat, and names downstream tools (omniseek_coauthors / omniseek_read) for drilling into the roster. It also warns that the roster is a starting point, not a verified membership list, which sets correct expectations.

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