deep_research

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

Without annotations, the description carries full burden. It discloses key behaviors: query decomposition, real-time web search, code execution when include_analysis=True, synthesis into reports with citations, and cost monitoring. It does not cover all traits (e.g., rate limits, auth), but the main behaviors are well communicated.

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 well-structured with clear sections (What it does, Best for, Returns, Note). Every sentence adds value, and the key information is front-loaded. It is appropriately concise.

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 complexity (5 params, output schema exists), the description covers behavior and return type reasonably but lacks parameter explanations for most fields. It omits details on async handling despite a callback_url. Combined with good output schema, it is partially 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?

Schema coverage is 0%, so description must explain all 5 parameters. Only include_analysis is partially described (when include_analysis=True). The other parameters (system_instructions, request_clarification, callback_url) are not explained, leaving significant gaps.

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 it performs autonomous deep research with web search and analysis, using a strong verb and resource. It does not explicitly differentiate from siblings like research_status or research_with_context, but the scope is clear enough.

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 'Best for' section lists ideal use cases (current events, data analysis, complex topics, academic research), providing clear context. However, no exclusions or direct comparisons to sibling tools are given, limiting guidance on when not to use.

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