search

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

With no annotations provided, the description fully discloses the tool's behavior: it extracts concepts, generates Boolean queries per strategy, runs them, dedupes by publication number, and costs 1 credit. It adds useful context beyond just 'search', such as the internal workflow and cost.

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, front-loading the purpose and then detailing the process and strategies. It is relatively concise, though it could be slightly tighter. Every sentence adds value.

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 no annotations and no output schema, the description covers essential aspects: processing steps, strategies, cost, and parameter constraints. It is complete enough for the tool's complexity, though it could mention potential errors or when to use siblings.

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?

Input schema coverage is 100%, so baseline is 3. The description adds meaning by explaining each parameter: 'description' as natural-language input, 'strategy' with three options and their meanings, and 'limit' as max hits. It enriches the schema descriptions, earning a 4.

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: executing a patent search against Google Patents server-side, processing a natural-language description and strategy, and returning ranked hits. It distinguishes itself from sibling tools like 'query' by specifying the server-side processing and deduplication.

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 explains when to use the tool (for patent searches with natural language input) and details the processing steps and strategies. However, it lacks explicit guidance on when not to use it or direct comparison to alternatives like the 'query' sibling tool.

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