start_deep_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 details key features like adaptive depth, source evaluation, and structured reporting, which adds useful context beyond basic functionality. However, it lacks information on performance aspects such as rate limits, execution time, or error handling, leaving gaps in behavioral understanding.

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 structured with bullet points but is overly verbose, listing features that could be condensed. Sentences like 'Works for any research type...' add redundancy. While front-loaded with a clear purpose, it includes excessive detail that doesn't all earn its place, reducing efficiency.

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 (deep research with multiple features) and no output schema, the description is moderately complete. It covers the process and features but lacks details on output format, error cases, or practical limitations. Without annotations, it should provide more behavioral context to be fully adequate.

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 has 100% description coverage for its single parameter 'research_question,' so the baseline score is 3. The description does not add any additional meaning or examples beyond what the schema provides, such as formatting guidelines or scope constraints for the research question.

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 'conducts comprehensive research on any topic with a systematic, balanced approach,' specifying the verb 'conduct research' and resource 'any topic.' It distinguishes itself by emphasizing depth and systematic methodology. However, without sibling tools, differentiation is not applicable, preventing a perfect score.

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 no explicit guidance on when to use this tool versus alternatives, as no sibling tools exist. It mentions it 'works for any research type' but lacks context on prerequisites, limitations, or specific scenarios where it's most effective, offering only implied usage without exclusions.

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