search_topics

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

The description discloses that the tool searches OpenAlex, filters papers since 2023, and sorts by citation count. This provides meaningful behavioral insight beyond the tool name, though it does not mention rate limits, caching, or result structure.

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 with two short paragraphs and a bulleted Args list. Every sentence adds value, and the main purpose is front-loaded in the first sentence.

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 simplicity (2 parameters, no output schema), the description provides sufficient context: source database, time filter, sorting criteria, and parameter details. It could be improved by briefly noting what the output contains (e.g., paper titles and citation counts).

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 adds significant meaning to the topic parameter by providing examples ('large language models', 'CRISPR') and explaining it as a subject area. For limit, it clarifies the default (10) and maximum (50), which goes beyond the schema's basic type and default.

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 finds the most-cited recent papers on a topic, specifying the source (OpenAlex), time range (since 2023), and sorting (by citations). This distinguishes it from sibling tools like search_papers, which likely perform broader searches.

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 says 'Ideal um Trend-Themen zu erkunden' (ideal for exploring trending topics), providing clear usage context. However, it does not explicitly mention when not to use this tool or suggest alternatives like search_papers for non-trending topics.

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