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patent_assignee_search

Read-onlyIdempotent

Find patent assignees (companies / organizations) by name fragment. Returns assignee id, organization name, location, and total patents owned. Ranked by patent count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return (default 25, max 100).
organizationYesCompany or organization name fragment (e.g. 'Apple', 'Genentech').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already carry the safety profile (readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds useful context beyond annotations: the ordering behavior ('Ranked by patent count') and the returned fields (assignee id, organization name, location, total patents owned). However, it doesn't disclose matching semantics (partial/fuzzy behavior), pagination, or behavior on zero matches. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, each earning its place: the action, the return payload, and the ordering. The main verb and resource are front-loaded in the first sentence, and there is zero filler or redundant restating of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity read-only search with fully documented parameters and safety annotations, the description covers the essential operating contract: what is searched, what is returned, and how results are sorted. Minor gaps: rank direction is only implied (descending by patent count), and exact name-matching behavior isn't specified. Since there is no output schema, listing the returned fields is a meaningful contribution.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: both 'organization' (name fragment with examples) and 'limit' (default 25, max 100) are fully documented in the schema. The description's 'by name fragment' merely echoes the schema's own wording and adds no new parameter meaning. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource+method: 'Find patent assignees (companies / organizations) by name fragment.' It explicitly scopes the tool to organizations serving as assignees, which distinguishes it from the patent siblings (patent_search, patent_inventor_search, patent_details, patent_recent) without needing to open any of them. An agent can tell this is not a general patent search or inventor search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no named alternatives, and no exclusions. Among 200+ siblings, the only differentiator is the implicit resource type ('patent assignees'), and the description never tells the agent to prefer this over patent_search or patent_inventor_search for related queries. The agent must infer usage context entirely.

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

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