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

Annotations already indicate read-only (readOnlyHint=true) and open-world (openWorldHint=true) behavior. The description adds the valuable detail that results are 'grounded' with source citations, which is a behavioral trait not present in the annotations. It does not mention potential internet latency, rate limits, or failure modes, but the added citation context is meaningful.

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?

Two sentences, with the core action and purpose in the first sentence, and usage contexts in the second. Every word contributes; no redundancy or fluff.

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 covers what the tool does, when to use it, and a key output trait (citations). No output schema exists, so a more detailed note about result format or pagination could improve completeness, but the description is sufficient for selecting and invoking the tool correctly.

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% coverage with descriptions for every parameter, including the research_type enum. The tool description adds no additional parameter meaning beyond pointing to the general purpose, so the baseline of 3 applies; the schema carries the burden.

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 performs web research on a company, trademark, or legal topic, with specific use cases (company background, recent news, common law trademark use, case law research). It distinguishes itself from sibling tools by focusing on internet-wide research rather than repository-specific lookups like search_trademarks or get_mark_ai_summary.

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 explicitly lists when to use the tool (company background, recent news, common law use, case law research) and the research_type enum reinforces these contexts. It does not explicitly state when not to use it or name alternatives, but the sibling tool names (e.g., search_trademarks, get_mark_ai_summary) imply that those are for different, more targeted tasks.

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