DataNexus MCP

legal_fetch_inventor_portfolio

Read-onlyIdempotent

Fetch the patent portfolio for a named inventor with optional assignee filter. Read-only. No side effects. Idempotent. inventor_name: Inventor surname or full name e.g. Smith or John Smith. Required. Fuzzy match — common names may return many results. assignee: Company or organisation name to narrow results e.g. Apple Inc. Optional. Returns patent numbers, titles, filing dates, jurisdictions, and current status. Use this when researching an inventor's work or a company's patent portfolio. Use legal_search_patents_by_keyword instead when you need patents by topic not by inventor. Verified source: EPO OPS + USPTO. 24-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="legal_fetch_inventor_portfolio", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`assignee`	No	Company name to filter results e.g. Apple Inc. Optional.
`inventor_name`	Yes	Inventor surname or full name e.g. John Smith. Required.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. Description adds fuzzy match disclaimer, data source, cache duration, and expected result fields, which are valuable 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.

Conciseness4/5

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

Description is relatively long but well-structured with clear sections (purpose, params, usage, source, feedback). Front-loads key info. Could tighten slightly but effective overall.

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

Completeness5/5

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

Covers all important aspects: fuzzy matching, result fields, data source, cache, alternative tool, feedback mechanism. No gaps given the tool's moderate complexity and presence of output schema.

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

Parameters4/5

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

Schema coverage is 100%. Description adds examples (e.g., inventor_name: 'Smith or John Smith'), clarifies fuzzy matching implications, and explains assignee optionality. Adds meaning beyond schema.

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?

Clearly states it fetches patent portfolio for a named inventor with optional assignee filter. Distinguishes from sibling legal_search_patents_by_keyword by specifying topic vs. inventor focus.

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

Usage Guidelines5/5

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

Explicitly says when to use (researching inventor or company portfolio) and when not (use legal_search_patents_by_keyword for topics). Includes feedback mechanism for gaps.

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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TDQS

A4.1/5.0

Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources

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