comprehensive_research

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

The description adds valuable behavioral context beyond annotations: it explains that the tool uses AI agents to 'automatically search multiple sources, analyze findings, and compile comprehensive reports.' This clarifies the multi-step, automated nature of the research process. Annotations already indicate it's read-only, non-destructive, open-world, and non-idempotent, so the description appropriately focuses on operational behavior without contradiction.

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 efficiently structured in two sentences: the first explains the core functionality, and the second provides usage context. Every phrase adds value without redundancy, and it's appropriately front-loaded with the main purpose.

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 (multi-step AI research), the description adequately covers the high-level process but lacks details about output format (no output schema exists), potential limitations, or error handling. With annotations covering safety aspects, the description provides reasonable context but could be more complete for such a sophisticated tool.

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?

With 100% schema description coverage, the input schema fully documents both parameters ('query' and 'modelClass' with enum values). The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline expectation without providing extra semantic value.

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 purpose: 'Perform in-depth research on complex topics using AI agents that automatically search multiple sources, analyze findings, and compile comprehensive reports.' It specifies the verb (perform research), resource (complex topics), and method (using AI agents). However, it doesn't explicitly differentiate from its sibling 'deep_search' tool, which likely has overlapping functionality.

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 implied usage guidance: 'Ideal for thorough investigations, market research, technical analysis, or any topic requiring deep understanding from multiple perspectives.' This suggests appropriate contexts but doesn't explicitly state when to use this tool versus the 'deep_search' sibling or other alternatives, nor does it mention any exclusions or prerequisites.

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