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patent-review

Get an external patent examiner review of a patent application

Install / Use

npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill patent-review

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Supported Platforms

OpenAI Codex

Our assessment of patent-review

patent-review scores 92/100 on our quality scale, 36th of 152 Education & Research skills we index (top 24%).

Its SKILL.md is 6.5 KB long, well organised into 22 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

With 16,644 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
18/20
Description
12/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 7 days ago, so patent-review is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

patent-review compared with similar skills

All 4 of these similar skills score higher than patent-review; compare them before choosing.

SkillScoreStarsUpdatedFormat
patent-review (this skill)by wanshuiyin9216.6k7d agoSKILL.md
Agent-Reachby Panniantong10085.5k11d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md
rufloby ruvnet10073.3k1d agoCLAUDE.md
last30days-skillby mvanhorn10062.9k3d agoCLAUDE.md

Frequently asked questions

How do I install patent-review?
Run npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill patent-review. The install tabs above show the steps for each supported agent.
Which AI agents does patent-review work with?
It is written for OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is patent-review safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is patent-review still maintained?
The repository was last updated 7 days ago, so patent-review is actively maintained.

name: patent-review description: "Get an external patent examiner review of a patent application. Use when user says "专利审查", "patent review", "审查意见", "examiner review", or wants critical feedback on patent claims and specification." argument-hint: "[patent-directory-or-scope]" allowed-tools: Bash(*), Read, Grep, Glob, Write, Edit, mcp__codex__codex, mcp__codex__codex-reply

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.

Step 3: Implement Fixes (Round 1)

Based on the examiner's office action:

  1. CRITICAL issues (102 rejection, 112 indefiniteness, missing enablement):

    • Must be fixed before proceeding
    • Amend claims or add specification support
  2. MAJOR issues (103 obviousness, weak claim scope, missing support):

    • Should be fixed or argued
    • Consider claim amendments or specification additions
  3. MINOR issues (language quality, numeral consistency, formatting):

    • Fix if time permits
    • Document in output for later cleanup

For each fix:

  • Show the specific change (old claim -> new claim)
  • Explain how the fix addresses the examiner's concern

Step 4: Round 2 — Follow-Up Review

Use mcp__codex__codex-reply with the threadId from Round 1:

mcp__codex__codex-reply:
  threadId: [from Round 1]
  # inherits the thread's model/effort — do not re-send
  prompt: |
    Here is the revised patent application after addressing your office action.

    CHANGES MADE:
    [list of all changes with rationale]

    REVISED CLAIMS:
    [updated claims]

    REVISED SPECIFICATION EXCERPTS:
    [changed sections]

    Please re-examine:
    1. Are the previous rejections overcome?
    2. Are there new issues introduced by the amendments?
    3. What is the updated patentability score?
    4. Any remaining grounds for rejection?

Step 5: Generate Improvement Report

Write patent/PATENT_REVIEW.md:

## Patent Review Report

### Application Summary
[Title, claims count, jurisdiction]

### Review Round 1
#### Office Action Summary
[Key findings from examiner]

#### Issues Found
| # | Type | Severity | Claim/Section | Issue | Citation | Fix Applied |
|---|------|----------|--------------|-------|----------|-------------|
| 1 | Clarity | CRITICAL | Claim 3 | Indefinite term "rapid" | 112(b) | Defined in spec |
| 2 | Novelty | MAJOR | Claim 1 | Ref X anticipates element C | 102 | Amended claim |

#### Score After Round 1: [X]/10

### Review Round 2
#### Follow-Up Assessment
[Are previous rejections overcome?]

#### Remaining Issues
[Any issues still outstanding]

#### Score After Round 2: [X]/10

### Recommendations
[Final recommendations before proceeding to jurisdiction formatting]
- [ ] All CRITICAL issues resolved
- [ ] All MAJOR issues resolved or argued
- [ ] Specification supports all claim amendments
- [ ] Ready for jurisdiction formatting

Key Rules

  • The reviewer persona must be a patent examiner, not a paper reviewer or academic.
  • Always use model_reasoning_effort: "xhigh" for maximum analysis depth.
  • Address CRITICAL and MAJOR issues before proceeding to the next phase.
  • Document all changes in the review report for traceability.
  • If the patentability score is below 5/10 after Round 2, recommend significant rework before filing.
  • The review is advisory -- actual prosecution may proceed differently.

Related Skills

View on GitHub
GitHub Stars16.6k
CategoryEducation
Updated7d ago
Forks1.4k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions