Auto Literature Screen

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

With no annotations, the description must disclose behavioral traits fully. It mentions multi-source search and internal processing but omits details like rate limits, authorization needs (apart from an optional API key), whether it is read-only, or if it is potentially long-running. The description provides basic transparency but lacks depth.

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, each adding value. It front-loads the main action and efficiently conveys the pipeline without redundancy. No waste.

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 tool's complexity (9 parameters, nested objects, no output schema), the description lacks details on output format, screening criteria behavior, ranking method, and potential limitations. It does not address the return structure, which is critical for an agent to use the result.

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 11%, so the description should compensate by explaining parameter roles. However, the description does not clarify the purpose of parameters like yearFrom, yearTo, limit, perSourceLimit, screeningCriteria, or semanticScholarApiKey. Only 'topic' is vaguely implied. This leaves many parameters underdocumented.

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 three specific sources (OpenAlex, Semantic Scholar, arXiv) and performs internal merge, dedupe, screen, and rank operations. It specifically says it returns only final selected papers, distinguishing it from sibling tools like discover_papers which likely do not screen.

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 does not provide any guidance on when to use this tool versus alternatives like discover_papers or expand_related_papers. It neither states prerequisites nor when not to use it, leaving the agent without decision criteria.

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