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

Annotations already indicate readOnlyHint=true and openWorldHint=true, aligning with the description's emphasis on research and evidence synthesis. The description adds context about returning a 'structured, audited deliverable' and server-side validation, but does not disclose additional behaviors like rate limits or authentication requirements.

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 relatively long and includes multiple example questions and a reference case, which aids clarity but also adds redundancy. It lacks a concise summary upfront and could be more focused on essential information.

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 (7 parameters, nested objects, no output schema), the description falls short. It does not explain the return format beyond 'structured, audited deliverable', nor does it describe the behavior of parameters like year_range or evidence_grade_required. The async parameter is only documented in the schema, not in the description.

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 14% (only the 'async' parameter has a description). While the description lists some parameters in examples (research_question, focus_domain, max_papers, etc.), it does not explain their semantics or provide context beyond indicating they are documented fields. This is insufficient compensation for the low schema coverage.

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 identifies the tool as a literature synthesis tool (PaperQA2) that returns a structured, audited deliverable. It lists specific use cases like literature review, hypothesis evaluation, contradiction mapping, and interdisciplinary synthesis, making its purpose unambiguous and distinct from sibling tools.

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 provides explicit example questions for when to use the tool (e.g., 'Conduct a literature review on <topic>', 'Evaluate the current hypothesis that <claim>'). However, it does not specify when not to use it or mention alternative tools (like 'sci_literature_search'), lacking explicit exclusion criteria.

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