google_research

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It extensively details the multi-agent process (Lead Researcher, Search Subagents, Citation Agent, Memory Module), the iterative workflow, and adaptive stopping criteria. This provides transparency about the tool's internal operations and potential for extensive parallel searches, beyond what any annotation could offer.

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?

Although long, the description is well-structured with clear headings, bullet points, and a step-by-step process flow. It front-loads the core purpose and then provides detailed but purposeful elaboration. Every section (Process Flow, Depth Levels) adds significant value without 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?

The description thoroughly covers the tool's behavior and process, but does not specify the structure or format of the final report beyond mentioning that citations are inserted and results are synthesized. Since there is no output schema, this gap is notable but not critical given the extensive process description.

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 describes 'topic' and 'max_content_per_page' but only provides an enum for 'depth' without explanation. The description adds meaningful semantics by explaining each depth level's iteration count, number of aspects, and coverage thresholds, thereby enriching the depth parameter beyond the schema.

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 extensive DEEP research on a topic using Anthropic's Multi-Agent Research Architecture.' It specifies the action (perform research), resource (topic), and the multi-agent nature, distinguishing it from simpler search tools like google_search or web_search.

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 conveys that this tool is for extensive, deep research, and outlines depth levels (basic, moderate, comprehensive) with iteration and coverage thresholds. It implies usage for complex, multi-faceted research needs, but does not explicitly exclude alternatives such as quick searches or single-aspect deep dives.

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