research_deep_search

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 mentions automation but lacks details on permissions, rate limits, data sources, or what 'import findings' entails (e.g., format, storage location). This is inadequate for a tool that likely involves external web access and data mutation.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and outcome, making it easy to parse quickly.

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 of web research and data import, with no annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't cover behavioral aspects like error handling, data formats, or integration with sibling tools, leaving significant gaps for agent usage.

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 description coverage is 50% (only 'topic' has a description). The description adds no parameter-specific information beyond implying 'topic' is for research queries and 'notebook_id' might be for output storage. It partially compensates but doesn't fully address the undocumented 'notebook_id' parameter.

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 action ('conduct deep web research and import findings') and resource ('findings'), specifying it's automated. However, it doesn't distinguish this from sibling tools like 'add_source_content' or 'generate_study_material', which might have overlapping functionality with research operations.

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 guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as how it differs from 'research_notebook_create' or 'add_source_content' for handling research data.

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