Discover Papers

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

With no annotations, the description must disclose all behavioral traits. It mentions internal steps (keeping candidates) but omits side effects, permissions, rate limits, or return structure. For a 9-parameter tool, this is insufficient transparency.

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 at two sentences, front-loading the alias information. It is well-structured but sacrifices necessary depth for brevity.

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 complexity (9 parameters, nested objects, no output schema, no annotations), the description is critically incomplete. It lacks return value description, parameter guidance, and usage prerequisites, making it inadequate for reliable agent invocation.

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 only 11% (only 'topic' described). The description adds no information about any parameters, failing to compensate for the low schema coverage. Parameters like 'screeningCriteria' need explanation but are entirely ignored.

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 it is an alias for auto_literature_screen and explains it keeps raw/deduped candidates internal and returns final selected papers. This effectively distinguishes it from sibling tools like expand_related_papers by specifying the internal process and output.

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 only notes it is an alias for auto_literature_screen but provides no guidance on when to use this tool versus alternatives. It does not mention any conditions or exclusions, leaving the agent without decision-making support.

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