kr-patent-prior-art-report

kr-patent-prior-art-report is a skill for Claude Code, Codex from lsj4232/KR_PATENT_SKILL. It costs 391 tokens per session (3,393 once invoked), scanned A, original, MIT.

A workflow that turns a Korean patent document into a prior-art research package for an expedited examination request. Prior art means earlier patents or other public technical documents that may relate to an invention.

In plain words
What is it for?
Use it to extract claims from a Korean patent specification, search and verify related patents, download their PDFs, create a comparison report, and fill the required application explanation document.
Why use it?
Patent applications need evidence about earlier technology and clear comparisons with the application's claims. This workflow gathers and verifies four patent documents and prepares supporting files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to extract claims from a Korean patent specification, search and verify related patents, download their PDFs, create a comparison report, and fill the required application explanation document.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report
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 lsj4232/KR_PATENT_SKILL --skill kr-patent-prior-art-report
Clone the repo
git clone --depth 1 https://github.com/lsj4232/KR_PATENT_SKILL

Made for: Claude Code, Codex.

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 kr-patent-prior-art-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report/github.svg)](https://agentmods.dev/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report)
Your own site
<a href="https://agentmods.dev/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report"><img src="https://agentmods.dev/badge/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report/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 kr-patent-prior-art-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report"><img src="https://agentmods.dev/badge/skills/lsj4232/kr_patent_skill/kr-patent-prior-art-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 391 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,393 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • 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 $0.00391 $0.03393
Opus 5 $0.00196 $0.01697
Sonnet 5 $0.00078 $0.00679
Haiku 4.5 $0.00039 $0.00339

Measured 12d ago against content hash a6d7440d27d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

kr-patent-prior-art-report scanned grade A with 1 finding 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 12d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/build_hwpx.py, scripts/extract_docx_text.py, scripts/measure_pages.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sL -o "선행특허 N_{cc}{번호}{종별}.pdf" "https://patentimages.storage.googleapis.com/..."
kr-patent-prior-art-report/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

kr-patent-prior-art-report — 우선심사용 선행기술 조사 패키지 생성

입력 / 산출물

입력: 한국 특허 명세서 .docx (청구항 포함), 케이스 폴더 경로 (docx가 있는 폴더가 기본)

산출물 (모두 케이스 폴더에 저장):

  1. 선행특허 1_{cc}{번호}{종별}.pdf ~ 선행특허 4_...pdf — 공보 원문 4건
  2. [{REF}]선행기술조사_{발명의 명칭}.md — 조사 보고서
  3. [OUR_REF]우선심사신청설명서.hwpx — 특허청 양식 설명서 (파일명 고정: 리터럴 "[OUR_REF]")

워크플로우

1단계: 명세서 파악

python scripts/extract_docx_text.py "<명세서.docx>" <scratchpad>/spec.txt
  • Grep으로 【청구항, 【발명의 명칭】 위치 확인 후 청구항 전체와 과제해결수단을 Read.
  • 독립항 번호(인용 문구 없는 항: 통상 방법/시스템/프로그램 3건)와 핵심 구성요소를 목록화한다. 핵심 구성요소는 이후 문헌 선정의 커버리지 기준이 된다.
  • 특징적 종속항(차별화 포인트가 되는 항)도 2~3개 뽑아둔다.

2단계: 선행특허 4건 검색·검증 (WebSearch + WebFetch)

  • WebSearch로 patents.google.com을 대상으로 검색한다. 검색어는 핵심 구성요소별로 국문/영문/중문을 섞어 여러 번 fan-out (예: "볼트 체결 딥러닝 검사 patents.google.com", ""bolt loosening" detection deep learning patent KR").
  • 선정 원칙:
    • 총 4건. 각 문헌이 서로 다른 핵심 구성요소를 커버하도록 분산 배치 (예: 센서 측정 / AI 판정 / 설계 대비 비교 / 개별 요소기술).
    • 국가 혼합 권장 (예: 중국 공개 1건 + 한국 등록/공개 3건). 등록특허 우선.
    • 반드시 실존 특허여야 함 — 후보마다 patents.google.com/patent/{번호}/{ko|en}을 WebFetch로 열어 서지사항(명칭·출원인·공개/공고일·청구항 1·법적상태)과 patentimages PDF 링크를 확인한다. 검증 안 되면 교체.
  • 각 문헌에 대해 대비 청구항 매핑을 정한다 (독립항 중심, 종속항 보강).

3단계: PDF 다운로드

curl -sL -o "선행특허 N_{cc}{번호}{종별}.pdf" "https://patentimages.storage.googleapis.com/..."
  • 파일명 규칙: 한국 등록 kr2292602b1 (등록번호 7자리+종별, "10-" 접두 제거), 한국 공개 kr20180131471a, 중국 cn118654725a. 영문 번역본이면 _en 접미.
  • 다운로드 후 각 PDF의 페이지 수를 검증한다 (1~2페이지면 다운로드 실패 의심):
python -c "import re; d=open('파일.pdf','rb').read(); print(len(re.findall(rb'/Type\s*/Page[^s]', d)))"

4단계: 조사 md 작성

파일명: [{REF}]선행기술조사_{발명의 명칭}.md. 구성 (KIPO 우선심사 자체조사 양식 준용):

# [{REF}] 선행기술 조사 — {발명의 명칭}
대상 출원: ... (독립항: 청구항 X(방법), Y(시스템), Z(프로그램))

【검색결과】
1. 중국 공개특허 제XXXXXXXXX호 (YYYY.MM.DD. 공개)   ← 공개특허는 "공개", 등록특허는 "공고"
2. 한국 등록특허 제10-XXXXXXX호 (YYYY.MM.DD. 공고)
...
* 문헌 서지 정보: 번호/명칭/출원인/첨부 PDF 파일명

【선행기술과의 대비설명】
| 청구항 | 선행기술 문헌명 | 유사점 | 차이점 | 대비 판단 |  ← 문헌별 1행, 총 4행

## 종합 의견 (어느 문헌에도 개시되지 않은 본원 통합 구성 정리)

Read the full file on GitHub · 172 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 172 lines · 391 tokens per session scan A a6d7440d27d5

Subscribe to this mod's changes

kr-patent-prior-art-report is a skill published in the GitHub repository lsj4232/KR_PATENT_SKILL (15 stars, last pushed 19d ago), licensed MIT. It adds 391 tokens to every session and 3,393 once invoked, about $0.0020 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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