research_topic

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

With no annotations, the description transparently reveals it searches OpenAlex, uses Unpaywall for OA status, and extracts abstracts from search responses. It does not mention read-only nature, error handling, or rate limits, but the workflow is clearly non-destructive and well-outlined.

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 two sentences, front-loaded with the core workflow, and every sentence adds value. No unnecessary words or repetition.

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 main workflow, data sources, and abstraction sourcing. With an output schema present, return values are documented elsewhere. Missing details about potential errors or authentication are minor given the tool's simplicity.

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 coverage is 100%, so parameters are well-documented in the schema. The description adds context by linking query to OpenAlex search and mentioning top results, but does not provide deeper semantics beyond what the schema already offers.

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 is a convenience workflow that searches OpenAlex for a query, fetches OA status for top results, and returns a compact overview. It distinguishes from sibling tools like search_papers and get_paper by combining search and OA enrichment in a single step.

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 the tool is for quickly assessing a research area but does not explicitly state when to use it versus alternatives like search_papers or get_paper. No exclusions or conditional guidance is provided.

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