keiro_research_pro

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

With no annotations, the description carries the full burden. It discloses the tool's output behavior (detailed analysis, multiple perspectives, data visualizations, source evaluation) but does not mention side effects, limitations, or any safety traits. This is partial but reasonable for a research tool.

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 sentences with no filler. It front-loads the key capabilities and closes with a clear usage context, making it efficient and well-structured.

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?

For a single-parameter research tool, the description provides a solid understanding of expected outputs and target scenario. It could further differentiate from sibling tools like 'keiro_search_pro,' but the 'complex research tasks' context and feature set make it adequately complete.

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 schema already provides a full description for the single 'query' parameter ('The research topic or question'), achieving 100% coverage. The tool description adds no additional parameter semantic detail, so the baseline score of 3 applies.

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 indicates the tool performs research with detailed analysis, multiple perspectives, data visualizations, and source evaluation. It distinguishes itself from the simpler 'keiro_research' via 'Advanced' and 'For complex research tasks,' though the verb is implicit rather than explicit.

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 phrase 'For complex research tasks' provides clear context on when to use this tool. It does not explicitly mention when not to use it or name alternatives, but the guidance is sufficient for general targeting.

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