搜索学术论文

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 only states that the tool searches papers on a specified platform and does not mention any behavioral traits such as pagination, rate limits, authentication requirements, or result format. This minimal disclosure is insufficient for a tool with potential side effects or complex behaviors.

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 short sentences, efficiently front-loaded with the primary action and immediately providing a relevant pointer to recommend_platforms. Every word earns its place; there is no fluff or repetition of the title.

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 (6 parameters, nested filters object, and an output schema), the description is severely incomplete. It lacks any mention of return values, parameters, pagination, or usage scenarios beyond the platform recommendation. The agent cannot confidently invoke this tool based solely on this description, especially with no annotation support.

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 input schema has 6 parameters with 0% description coverage, so the description must compensate by explaining parameter meaning. It only references the platform implicitly ('specified platform') and does not describe query, year, limit, cursor, or filters. This leaves the agent without enough semantic understanding of the parameters, warranting a low score.

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 that the tool searches for academic papers on a specified platform, using the specific verb 'search' and resource 'academic papers'. It distinguishes from siblings like recommend_platforms, download_paper, and read_paper by focusing on the search action, making the purpose unmistakable.

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 explicitly instructs using recommend_platforms to get recommended platforms, providing a clear prerequisite for when to use this tool. However, it does not explicitly mention when not to use this tool or how it relates to download_paper/read_paper, leaving some gaps but still offering actionable context.

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