patents

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 indicates this is a read operation ('Get') and specifies the scope ('US patent'), but doesn't mention potential limitations like rate limits, authentication requirements, error conditions, or whether the data is real-time. The description adds basic context but lacks comprehensive behavioral traits.

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 efficiently structured in two sentences: the first states the purpose and parameter, the second lists the returned fields. Every element serves a purpose with zero wasted words, making it appropriately sized and front-loaded with the core functionality.

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 tool's low complexity (single parameter, no output schema, no annotations), the description provides adequate context for basic usage. It covers what the tool does, what parameter it needs, and what data it returns. However, without an output schema, it could benefit from more detail about the return structure beyond the field names listed.

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 100% with the single parameter 'number' well-documented in the schema. The description adds minimal value beyond the schema by mentioning 'patent number' and providing an example format in parentheses, but doesn't significantly enhance parameter understanding beyond what the structured schema already provides.

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 verb ('Get full details') and resource ('specific US patent'), specifying it's for a single patent identified by number. It distinguishes from sibling tools search_inventors and search_patents by focusing on retrieval of complete information for a specific patent rather than searching across multiple patents or inventors.

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 implies usage context by specifying 'by patent number' and listing the returned fields, suggesting this tool should be used when you have a specific patent number and need comprehensive details. However, it doesn't explicitly state when NOT to use it or name alternatives like the sibling search tools, missing full explicit guidance.

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

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

No annotations are provided, so the description carries the full burden. It mentions the return data (inventor name, location, patent numbers) but does not disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, error handling, or pagination details beyond the 'per_page' parameter in the schema.

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 two sentences with zero waste: the first sentence states the purpose and scope, and the second specifies the return values. It is appropriately sized, front-loaded with key information, and efficiently structured.

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 provides basic purpose and return data, but lacks details on behavioral aspects like safety, performance, or error handling. For a search tool with two parameters and 100% schema coverage, it is adequate but has clear gaps in transparency.

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 100%, so the schema already documents both parameters ('query' and 'per_page') with their types and descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema coverage.

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 specific action ('Search'), resource ('US patent inventors'), and filtering criterion ('by last name'), distinguishing it from sibling tools like 'get_patent' (likely retrieves a single patent) and 'search_patents' (searches patents rather than inventors). It provides a complete picture of what the tool does.

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 implies usage for searching inventors by last name, but does not explicitly state when to use this tool versus alternatives like 'search_patents' or provide any exclusions or prerequisites. The context is clear but lacks explicit guidance on tool selection.

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

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

No annotations are provided, so the description carries the full burden. It mentions the search scope (US patents, abstracts) and return fields, but lacks behavioral details such as pagination behavior (implied by 'per_page' parameter), rate limits, authentication needs, or error handling. The description adds some context but is insufficient for a mutation-free tool with no annotation coverage.

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 two concise sentences with zero waste: the first states the action and scope, the second lists return fields. It is front-loaded and appropriately sized for a simple search tool, with every sentence earning its place.

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 tool's low complexity (search with 2 parameters), 100% schema coverage, and no output schema, the description is minimally adequate. It covers purpose and return fields but lacks behavioral context (e.g., pagination, limits) and explicit usage guidelines. Without annotations, it should do more to compensate, but it meets the baseline for a simple tool.

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 100%, so the schema already documents both parameters ('query' and 'per_page') with descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as search syntax or result ordering. Baseline 3 is appropriate when the schema does the heavy lifting.

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 searches US patents by keyword, matching against abstracts, and returns specific fields (patent number, title, date, inventors, assignee). It distinguishes from 'get_patent' (likely a detail lookup) and 'search_inventors' (inventor-focused search), though not explicitly. The purpose is specific but lacks explicit sibling differentiation.

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 implies usage for keyword-based patent searches against abstracts, but does not explicitly state when to use this tool versus alternatives like 'search_inventors' or 'get_patent'. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the tool name and description.

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