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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that results are deduplicated and can be inspected, saved, expanded via references, or used for author exploration, which adds useful context beyond a simple 'search' and implies read-only behavior.

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 concise and front-loaded, with two sentences that pack in purpose, outcomes, and parameter guidance. Every clause adds value, and the engine list is efficiently embedded.

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 covers the core usage, result handling, and key parameter specifics, while the output schema handles return details. It misses only minor aspects like limit semantics and pagination, which are minor given the default value and typical search behavior.

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 description explains that query can be keywords, a DOI, or a person name, and provides an explicit comma-separated subset for engines, effectively compensating for the schema's lack of descriptions. However, it does not mention the limit parameter, leaving it unexplained despite the 0% schema coverage.

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's action: 'Start a research traversal' from keywords, DOI, or person name. It distinguishes itself from sibling tools by positioning this as the entry point for research exploration, while other tools like doi_lookup or author_candidates handle more specific steps.

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 provides implied usage context (use to begin research) and gives explicit guidance on the engines parameter, including a list of allowed values. However, it does not explicitly mention when not to use this tool or name alternatives, such as using scholarfetch_doi_lookup for direct DOI lookup.

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