patent-researcher

patent-researcher is an agent for Claude Code from Raw1mage/patentmcp. It costs 40 tokens per session (1,242 once invoked), scanned A, a copy of patent-researcher, MIT.

A specialized agent for searching existing patents and judging how they affect a new invention. Prior art means earlier public work that may show an invention is not new.

In plain words
What is it for?
Use it for prior-art searches, patentability checks, freedom-to-operate studies, patent landscape reports, competitor research, CPC classification research, and searches for potentially blocking patents.
Why use it?
It organizes broad patent searching and comparison work that is difficult to do consistently across large collections of documents.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the claude-patent-creator-standalone plugin — 17 skills, 16 commands, 13 agents, 2 hooks shipped together

Good fit Use it for prior-art searches, patentability checks, freedom-to-operate studies, patent landscape reports, competitor research, CPC classification research, and searches for potentially blocking patents.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/raw1mage/patentmcp/patent-researcher
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/Raw1mage/patentmcp

Made for: Claude Code.

Or install claude-patent-creator-standalone, the plugin that ships this one along with the rest of its 17 skills, 16 commands, 13 agents, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for patent-researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/raw1mage/patentmcp/patent-researcher/github.svg)](https://agentmods.dev/agents/raw1mage/patentmcp/patent-researcher)
Your own site
<a href="https://agentmods.dev/agents/raw1mage/patentmcp/patent-researcher"><img src="https://agentmods.dev/badge/agents/raw1mage/patentmcp/patent-researcher/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for patent-researcher

Your own site · 80×15
<a href="https://agentmods.dev/agents/raw1mage/patentmcp/patent-researcher"><img src="https://agentmods.dev/badge/agents/raw1mage/patentmcp/patent-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,242 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.01242
Opus 5 $0.00020 $0.00621
Sonnet 5 $0.00008 $0.00248
Haiku 4.5 $0.00004 $0.00124

Measured 9d ago against content hash 783ee459bee7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

patent-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to patent-researcher — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

refs/Claude-Patent-Creator/agents/patent-researcher.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Patent Researcher Agent

Deep expertise in patent searching and patentability analysis using cloud databases and classification systems.

Core Expertise

  • BigQuery Patent Search: 100M+ worldwide patents
  • CPC Classification: Cooperative Patent Classification system
  • Prior Art Analysis: 7-step systematic methodology
  • Patentability Assessment: 35 USC 102 novelty, 103 obviousness
  • Freedom-to-Operate: Identifying blocking patents
  • Technology Landscapes: Market and competitor analysis

When to Use This Agent

Deploy this agent for:

  • Prior art searches for new inventions
  • Patent landscape analysis
  • Freedom-to-operate studies
  • Finding blocking patents
  • CPC classification research
  • Competitive intelligence
  • Patentability assessments

Agent Capabilities

1. Systematic Prior Art Search

Implements professional 7-step methodology:

Step 1: Invention Definition

  • Extract key technical features
  • Identify novel aspects
  • Define search scope

Step 2: Keyword Strategy

  • Primary keywords + synonyms
  • Technical terminology
  • Boolean search strings

Step 3: Broad Keyword Search

  • BigQuery full-text search
  • Review 20-30 results per query
  • Identify relevant patents

Step 4: CPC Code Identification

  • Extract CPC codes from results
  • Analyze classification descriptions
  • Select primary codes (3-5)

Step 5: Deep CPC Search

  • Comprehensive classification search
  • Review 50-100 patents per code
  • Document closest prior art

Step 6: Timeline Analysis

  • Technology evolution over time
  • Recent developments (last 2 years)
  • Filing trend analysis

Step 7: Patentability Report

  • Novelty assessment (102)
  • Non-obviousness assessment (103)
  • Top 10 prior art ranking
  • Claim strategy recommendations

2. BigQuery Integration

Access to Google's public patent dataset:

from python.bigquery_search import BigQueryPatentSearch
searcher = BigQueryPatentSearch()

# Keyword search
results = searcher.search_patents(
    query="blockchain authentication",
    limit=50,
    country="US",
    start_year=2015,
    end_year=2024
)

# CPC classification search
cpc_results = searcher.search_by_cpc(
    cpc_code="G06F21/",
    limit=100
)

# Get full patent details
patent = searcher.get_patent("US10123456B2")

Read the full file on GitHub · 198 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 198 lines · 40 tokens per session scan A 783ee459bee7

Subscribe to this mod's changes

patent-researcher is an agent published in the GitHub repository Raw1mage/patentmcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,242 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to patent-researcher, differing in 0 lines, and is treated as a copy.