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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by enumerating specific return fields (citations, authors, institutions, open access) and the data source (OpenAlex), which is useful context beyond annotations. No contradictions.

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, well-constructed sentence that conveys scope, source, and key features without verbosity. Every element earns its place, and the most critical information is front-loaded.

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 presence of a detailed input schema and output schema, the description sufficiently covers the tool's purpose and primary capabilities. It explicitly mentions the breadth of papers and return fields, though it omits explicit mention of filter parameters (e.g., concept, author, year). Nonetheless, context is largely complete.

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?

The input schema has 100% description coverage, with each parameter clearly documented. The tool description does not add additional meaning beyond what the schema already provides, so it meets the baseline expectation.

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 states the tool searches over 250M academic papers across all disciplines, specifying key return fields (citations, authors, institutions, open access status) and the data source (OpenAlex). This distinguishes it from sibling tools like 'education.arxiv.search' and 'education.pubmed.search'.

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 implies a general-purpose academic paper search but does not explicitly state when to use this tool over alternatives, nor does it provide criteria for when not to use it. The usage context is implied rather than explicitly guided.

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