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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals key behaviors: papers are sorted by citation count, data comes from OpenAlex with CC0 license, and the corpus covers multiple fields. It does not describe error handling, authentication, or rate limits, but for a read-only metadata retrieval tool, the disclosed sort order and data source provide solid behavioral context.

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 and front-loaded: first sentence states core function and data fields, second gives scope and browsing/filtering modes, third covers sorting, source, and usage context. Every sentence adds value, and the length is appropriate for the tool's 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?

The description provides sufficient context for an agent to invoke the tool: it explains what fields are returned, how results are sorted, where data comes from, and when to use it. It lacks explicit return format details, but no output schema exists and the metadata field list partially compensates. The minor or/combines ambiguity with query and topic is the main gap.

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 baseline is 3. The description adds example topic IDs and clarifies that topic browsing and keyword filtering are possible, but it introduces ambiguity by saying "Browse by ... or filter by" while the schema states query "combines with topic to narrow results." It does not meaningfully enhance parameter understanding beyond the 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 clearly states the tool returns academic paper metadata with specific fields (title, abstract, authors, citations, DOI, open access URL) and that papers are sorted by citation count. It identifies the resource and scope (27M+ works, all fields), making the purpose unambiguous. However, it does not explicitly distinguish itself from sibling tools like article, search, or lookup, so it falls short of full sibling differentiation.

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 includes an explicit usage trigger: "Use this when the user needs scholarly references, citation counts, or research context that Wikipedia does not cover." This gives clear context for when to select the tool. It does not mention alternatives or scenarios where a sibling tool would be preferable, so there are no exclusions or when-not-to-use guidance.

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