keiro_research

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 does disclose the return structure (summary, key points, timeline, cited sources), which is useful. However, it does not reveal potential limitations such as runtime, data source reliability, or any side effects, leaving the tool's operational behavior less transparent than it could be.

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 concise sentences that are front-loaded with the core purpose, followed by the return value and a use case. Every sentence contributes meaningful information without waste or redundancy.

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 tool with a single parameter and no output schema, the description covers the essential information: what it does and what it returns. It lacks explicit comparison to sibling tools or any caveats about usage, but is largely complete for a tool of this simplicity.

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 already provides a description for the only parameter ('The research topic or question'), achieving 100% coverage. The description adds minimal extra meaning beyond that, only broadening it with 'any topic'. This does not significantly enhance the parameter semantics beyond the schema baseline.

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 the tool's primary function ('Conduct comprehensive research on any topic') and specifies the return components ('detailed summary, key points, timeline, and cited sources'). It differentiates from search-like siblings by emphasizing 'comprehensive research' and 'in-depth analysis', but does not explicitly distinguish it from the similarly named keiro_research_pro.

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 implies usage context with 'Perfect for in-depth analysis', but provides no explicit guidance on when to use this tool versus alternatives like keiro_search, keiro_search_pro, or keiro_research_pro. It lacks exclusions or when-not-to-use information.

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