patent-review

patent-review is a skill for Claude Code from wanshuiyin/Auto-claude-code-research-in-sleep. It costs 50 tokens per session (1,674 once invoked), scanned A, original, MIT.

A workflow that reviews a patent application as a patent examiner would. A patent examiner is the official who checks whether an application meets the legal requirements for patent protection.

In plain words
What is it for?
Use it to examine claims, the specification, figure references, the prior-art report, and the invention disclosure through two review rounds.
Why use it?
It provides critical feedback on claims and the technical description before filing or further revision. The review is based on the application materials and known earlier work.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Codex.

Good fit Use it to examine claims, the specification, figure references, the prior-art report, and the invention disclosure through two review rounds.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review
About the project

ARIS is a collection of Markdown-based skills that define a workflow for autonomous machine-learning research, including idea discovery, experiment automation, and review loops. Researchers and AI coding agents use it across tools such as Claude Code, Codex, Cursor, and OpenClaw without depending on a single framework. The catalogue entries are ARIS workflow skills and agents.

wanshuiyin/Auto-claude-code-research-in-sleep · 16,030 stars · on GitHub

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.

Any agent
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill patent-review
Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep

Made for: Claude Code.

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-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review/github.svg)](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review)
Your own site
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review/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-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/patent-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,674 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. Third-party audits
  • Socket warn 14 May 2026
  • Snyk pass 14 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.00050 $0.01674
Opus 5 $0.00025 $0.00837
Sonnet 5 $0.00010 $0.00335
Haiku 4.5 $0.00005 $0.00167

Measured today against content hash 8c02c3040f0f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

patent-review 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 today.

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

Copies of this mod

1 near-identical copy found in the catalogue:

skills/patent-review/SKILL.md · 204 lines

How it starts

The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Patent Examiner Review via Codex MCP (xhigh reasoning)

Get a multi-round patent examiner review of the patent application based on: $ARGUMENTS

Adapted from /research-review. The reviewer persona is a patent examiner, not a paper reviewer.

Constants

  • REVIEWER_MODEL = gpt-6-astra — Model used via Codex MCP
  • REVIEW_ROUNDS = 2 — Number of review rounds
  • EXAMINER_PERSONA = "patent-examiner" — GPT-6-Astra persona

Prerequisites

  • Codex MCP Server configured:
    claude mcp add codex -s user -- python3 "$HOME/aris_repo/mcp-servers/codex-exec/server.py"   # your ARIS clone's path
    

Inputs

  1. patent/CLAIMS.md — all drafted claims
  2. patent/specification/ — all specification sections
  3. patent/figures/numeral_index.md — reference numeral mapping
  4. patent/PRIOR_ART_REPORT.md — known prior art
  5. patent/INVENTION_DISCLOSURE.md — invention structure

Workflow

Step 1: Gather Patent Context

Before calling the external reviewer, compile a comprehensive briefing:

  1. Read all claims (independent + dependent)
  2. Read specification sections (at least summary and detailed description)
  3. Read prior art report for context
  4. Identify: core inventive concept, claim scope, known prior art, target jurisdiction

Step 2: Round 1 — Full Examiner Review

Send to REVIEWER_MODEL via mcp__codex__codex with xhigh reasoning:

mcp__codex__codex:
  model: gpt-6-astra
  config: {"model_reasoning_effort": "xhigh"}
  prompt: |
    You are a senior patent examiner at the [USPTO/CNIPA/EPO].
    Examine this patent application and issue a detailed office action.

    CLAIMS:
    [all claims]

    SPECIFICATION SUMMARY:
    [key sections: title, technical field, background, summary, abstract]

    PRIOR ART KNOWN:
    [prior art references]

    PATENTABILITY STANDARDS TO APPLY:
    [US: 35 USC 101/102/103/112 | CN: Articles 22, 26 | EP: Articles 54, 56, 83, 84]

    Please issue an office action covering:

    1. CLAIM CLARITY (112(b)/Art 84):
       - Are all terms definite?
       - Any indefinite functional language?
       - Antecedent basis issues?

    2. WRITTEN DESCRIPTION (112(a)/Art 83 first para):
       - Does the spec support ALL claim scope?
       - Any claim elements without spec support?

    3. ENABLEMENT (112(a)/Art 83):
       - Can a POSITA practice the invention?
       - Any missing algorithm/structure for functional claims?

    4. NOVELTY (102/Art 54):
       - Would any known reference anticipate any claim?
       - Identify the closest single reference.

    5. NON-OBVIOUSNESS (103/Art 56):
       - Would any combination render claims obvious?
       - What is the motivation to combine?

    6. CLAIM SCOPE:
       - Are independent claims broad enough to be commercially valuable?
       - Do dependent claims provide meaningful fallback positions?
       - Any claims that are too broad (likely rejected) or too narrow (not valuable)?

    7. SPECIFICATION QUALITY:
       - Language issues (subjective terms, relative terms, result-to-be-achieved)
       - Reference numeral consistency
       - Missing embodiments

    Format your response as a formal office action with:
    - GROUNDS OF REJECTION for each issue (cite statute)
    - SUGGESTED AMENDMENTS for each issue
    - OVERALL PATENTABILITY SCORE: 1-10

    Be rigorous and specific. This is a real examination.

Read the full file on GitHub · 204 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. today Changed 8c02c3040f0f
  2. 5d ago Changed 69b9d09cf150
  3. 13d ago First seen · 204 lines · 50 tokens per session scan A dceadf86a54b

Subscribe to this mod's changes

patent-review is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (16,030 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 1,674 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.