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

Annotations already declare readOnly, openWorld and non-destructive. The description adds one meaningful behavioral caveat: results are source candidates, not dataset-fit approval, which warns against over-trusting output. It never explains what an 'availability state' looks like or how missing providers are represented.

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?

Two tight sentences, with the core action front-loaded and the caveat placed second where it reads as a qualifier. No filler, though it is arguably too terse for the information the agent needs.

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?

Placeholder.

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 0%, so the description carries full burden, yet it mentions neither the query parameter nor the scope enum (korean/international/all). Since there is no output schema explaining the returned records, the scope filter's effect on results is entirely undocumented.

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?

States a specific verb and resource: searching dataset/data-paper providers. The phrase 'explicit provider availability states' implies the domain differs from researchpilot_search_literature, but the sibling is never named, so differentiation is inferred rather than stated.

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?

No guidance on when to prefer this tool over researchpilot_search_literature or researchpilot_research_registry, and no prerequisites or exclusions. The agent must guess which search surface fits a dataset request.

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