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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses error semantics an agent needs: missing entities return not_found rather than a tool error, while API failures do raise errors. It also previews what each entity type returns (benchmark links, abstract/authors/PDF/code links, related benchmarks).

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?

Tight, front-loaded block with no filler sentences; each clause carries distinct information (identifier formats, per-type payloads, error behavior). It is dense to the point of being a single wall of text with four topics packed in, which slightly hurts scanability.

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 an output schema present, the description needn't restate return shapes, yet it adds useful per-type summaries and distinguishes not_found from tool errors. An agent has everything needed to call it correctly; only the pagination parameter remains unaddressed.

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 only 33%, but the description compensates well for the two required parameters: dataset identifiers must be family slugs not version slugs, papers use 24-character IDs not arXiv IDs, and task/domain use canonical slugs. Only the optional 'page' parameter is left unexplained.

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?

Opening sentence names a specific verb and resource (returns one exact research entity) and enumerates the four entity types. The word 'exact' signals it is a single-item lookup, which implicitly separates it from search_research, but that sibling is never named.

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?

Usage is implied rather than stated: 'one exact research entity' plus the identifier-format rules tell an agent this is a direct lookup requiring a canonical ID, so discovery-type queries belong elsewhere. No explicit when-not-to-use or named alternative (search_research, list_tasks) is given.

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