patents-trademarks-ip-mcp-server

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

Annotations already provide readOnlyHint=true and openWorldHint=true, indicating a safe read operation and open-ended results. The description does not add behavioral details beyond the annotations, such as result format or pagination, so it adds minimal extra value.

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 extremely concise: two short paragraphs, the first stating purpose, the second listing arguments. Every sentence is necessary and front-loaded, with no wasted words.

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 purpose, usage context, and parameters well. However, it lacks any mention of the return format or structure (no output schema). While not critical for a search tool, a brief note about results would improve completeness.

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?

Despite 0% schema description coverage, the description fully explains both parameters: assignee with examples and company context, max_results with range and default. This adds significant meaning beyond the schema's type-only definitions.

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 finds patents owned by a company (assignee) and specifies its utility for IP portfolio and competitive-intelligence research. This verb+resource combination is specific and distinguishes from sibling tools like get_patent_details (single patent) and search_patents (general 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 explicitly states the tool is useful for IP portfolio and competitive-intelligence research, providing clear context for its use. However, it does not explicitly state when not to use it or offer comparisons to alternatives, leaving some ambiguity.

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?

Annotations already provide readOnlyHint and openWorldHint, so the description adds limited behavioral context. It confirms a read operation but does not elaborate on the return metadata structure, which is a gap given no output 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 long with a bullet for parameter details, all front-loaded with the core purpose. Every word earns its place, and there is no redundant or vague language.

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?

For a simple one-parameter tool, the description is largely complete. However, without an output schema, it would benefit from briefly mentioning what metadata fields are returned to fully guide invocation.

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?

With 0% schema description coverage, the description compensates fully by explaining the patent_id parameter with concrete examples (e.g., 'US9876543B2'). This adds significant value beyond the schema's plain string type.

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 looks up a specific patent by its publication number and returns metadata, with examples for the input format. It is distinct from sibling tools which focus on searching by assignee or inventor.

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 when a specific patent number is known, but does not explicitly state when not to use it or provide alternatives. The context from siblings helps, but the description itself lacks direct 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?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description is consistent ('Find patents') but does not add behavioral details beyond what annotations and schema provide. No contradictions.

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 concise: a one-line purpose with use cases followed by parameter docs in a clear arg-style. No unnecessary words or repetition.

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?

For a simple search tool with no output schema, the description adequately covers purpose, parameters, and use cases. It could mention return format or pagination, but given the simplicity and sibling context, it is sufficiently complete.

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 0%, so the description fully compensates. It gives clear natural language explanations for both parameters: inventor with examples ('John Carmack', 'Shinya Yamanaka') and max_results with range and default ('1-30, default 15').

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 'Find patents by a named inventor' with specific verb and resource. It also mentions use cases (talent/expert discovery, prior-art research) that distinguish it from siblings like find_patents_by_assignee and search_patents.

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 calls out relevant scenarios (talent/expert discovery, prior-art research) but does not explicitly state when not to use it or compare to alternatives. However, the context provided is sufficient for an agent to infer appropriate usage.

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?

Annotations already indicate readOnlyHint=true and openWorldHint=true, covering safety and variability. The description adds return fields but no additional behavioral insights (e.g., rate limits, pagination). It is adequate but not enhanced beyond annotations.

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 succinct, with a clear two-part structure: purpose/return fields and parameter details. Every sentence adds 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?

For a search tool with two parameters and annotations, the description covers the key aspects: what it searches, parameters, and return fields. It lacks error handling or performance notes, but overall completeness is sufficient.

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?

With 0% schema description coverage, the description fully compensates: it explains query as free-text with examples, and max_results with range and default. This adds significant value beyond the schema's bare parameter definitions.

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 worldwide patents by various criteria (keyword, inventor, assignee, phrase) using Google Patents, listing specific return fields. This distinguishes it from sibling tools like find_patents_by_assignee and search_inventor, which are more targeted.

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 use for broad patent searches, and the sibling tools cover specific fields. However, it does not explicitly state when to prefer this tool over alternatives, such as using search_inventor for inventor-specific queries.

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