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deeparchi-ai

Patent MCP Server

by deeparchi-ai

get_cited_by

Retrieve patents that cite a given patent publication number. Returns citation count and citing patent details to trace downstream impact and prior art relationships.

Instructions

Get backward citations (who cites this patent). Returns cited_by_count (int) and cited_by_patents (list of {publication_number, title, assignee}). Extracted from Google Patents HTML.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
publication_numberYesPatent publication number, e.g. 'US-7650331-B1', 'CN-110286864-A'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.2

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the data source ('Extracted from Google Patents HTML') and enumerates return fields, implying a read-only scraping operation, but says nothing about auth, rate limits, missing-data behavior, or accuracy/freshness caveats.

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 tight sentences, front-loaded with the core purpose, then return shape, then provenance. Every sentence carries information; nothing is padded.

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 simple single-parameter read tool with no output schema, describing the returned fields (cited_by_count, cited_by_patents structure) closes the main information gap. Only the missing routing guidance against siblings keeps it from a 5.

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% and there is a single parameter with a concrete example format, so the schema fully documents the input. The description adds no format syntax or constraint beyond that, so baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource and clarifies direction with '(who cites this patent)', which is genuinely useful given the bidirectional_citation_graph sibling. It doesn't explicitly name the sibling alternatives (batch_get_cited_by, bidirectional_citation_graph), so it stops short of a 5.

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?

No when-to-use guidance, no exclusions, and no mention of batch_get_cited_by or bidirectional_citation_graph, which are the obvious alternative entry points for citation data. The agent must infer from the name alone when this single-patent version is preferable.

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