DataNexus MCP

legal_fetch_patent_by_number

Read-onlyIdempotent

Fetch full patent details by patent number and jurisdiction. Read-only. No side effects. Idempotent. patent_number: Patent number in EPODOC format e.g. EP1000000 for European, CN120586032 for Chinese, JP2020123456 for Japanese, WO2020123456 for PCT, US10000000 for US. Required. jurisdiction: Optional hint — one of EP, CN, JP, KR, US, WO, etc. Default EP. The tool normalises the patent number automatically; passing CN120586032 with jurisdiction EP is valid. Returns title, abstract, inventors, assignees, filing date, claims summary, and citation count. Use this when you have a specific patent number. Use legal_search_patents_by_keyword instead when you only have keywords and need to find patents. Verified source: EPO OPS. 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_patent_by_number", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`jurisdiction`	No	Patent office code: EP, US, WO. Default EP. Optional.	EP
`patent_number`	Yes	Patent number e.g. EP3456789 or US10123456. Required.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds further context: 'Read-only. No side effects. Idempotent', '24-hour cache', 'Verified source: EPO OPS', and normalisation behavior. 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.

Conciseness4/5

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

The description is ~150 words and well-structured: purpose, behavior, parameter details, return summary, usage contrast, source, caching, feedback. While slightly verbose, every sentence adds value and there is no redundancy. Could be trimmed slightly, but very effective.

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?

Given the presence of an output schema (not detailed but listed fields), the description covers return values (title, abstract, etc.), parameter constraints, caching policy, and a fallback feedback mechanism. For a tool with 2 parameters and clear purpose, this is highly complete.

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

Parameters5/5

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

Schema description coverage is 100%, but the description adds significant value: explains EPODOC format, provides concrete examples for each jurisdiction, clarifies optionality and default of 'jurisdiction', and states that passing mismatched jurisdiction is valid due to normalisation.

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 clearly states what the tool does: fetch full patent details by patent number and jurisdiction. It uses a specific verb ('fetch') and resource ('patent details'), and explicitly distinguishes itself from the sibling tool 'legal_search_patents_by_keyword' by stating when to use each.

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?

The description provides explicit usage guidance: 'Use this when you have a specific patent number. Use legal_search_patents_by_keyword instead when you only have keywords.' It also explains parameter behavior (automatic normalisation) and provides a feedback fallback mechanism.

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.

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