kr-patent-drawing-tagging

kr-patent-drawing-tagging is a skill for Claude Code, Codex from lsj4232/KR_PATENT_SKILL. It costs 270 tokens per session (3,001 once invoked), scanned A, original, MIT.

A tool for placing patent drawing reference numbers directly onto PNG images of diagrams. The numbers identify parts or blocks in a patent figure, and the tool also creates a mapping table.

In plain words
What is it for?
Use it to tag block diagrams, flowcharts, pipelines, and similar patent drawings from a confirmed numbering scheme and per-drawing mapping.
Why use it?
It adds labels to otherwise unmarked drawings while checking their positions against detected boxes and possible overlaps. This reduces manual placement work across multiple figures.

Skill for Claude CodeCodex

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

Good fit Use it to tag block diagrams, flowcharts, pipelines, and similar patent drawings from a confirmed numbering scheme and per-drawing mapping.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lsj4232/kr_patent_skill/kr-patent-drawing-tagging
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-drawing-tagging
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-drawing-tagging

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/lsj4232/kr_patent_skill/kr-patent-drawing-tagging"><img src="https://agentmods.dev/badge/skills/lsj4232/kr_patent_skill/kr-patent-drawing-tagging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 270 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,001 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
  • 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 $0.00270 $0.03001
Opus 5 $0.00135 $0.01501
Sonnet 5 $0.00054 $0.00600
Haiku 4.5 $0.00027 $0.00300

Measured 11d ago against content hash d8637145cd9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

kr-patent-drawing-tagging 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 11d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/tag_drawings_leader.py, scripts/tag_drawings.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.

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.

kr-patent-drawing-tagging/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

한국 특허 도면부호 태깅 (PNG 직접 삽입)

무엇을 하는가

무부호 도면 PNG(블록도·파이프라인도·흐름도)에 도면부호를 이미지 위에 직접 그려 넣어 태깅본 PNG를 만든다. 검증된 파이프라인 (사건 C, 도면 14장 / 부호 98개 실전 검증):

도면 시각 판독 → 부호 체계 확정 → 도면별 anchor 설정(JSON) 작성
→ scripts/tag_drawings.py 실행 (cv2 박스검출 + 최근접 매칭 + 충돌감지 배치)
→ 태깅본 전수 육안 검증 (Read로 이미지 확인) → 어긋난 도면만 설정 수정 후 재실행
→ 부호매핑표 md/xlsx 산출

작업 순서

Step 1. 입력 확보

  • 도면 PNG 폴더 (숫자 파일명 1.png, 2.png, … 권장)
  • 확정된 부호 체계 (없으면 kr-patent-symbol-design 먼저 호출)
  • 모든 도면을 Read로 시각 판독하여 각 박스의 위치를 파악해 둔다 (anchor 좌표의 근거).

Step 2. 설정 JSON 작성

examples/example_config.json 을 복사하여 사건별로 작성. 도면마다:

필드 의미
solo 태깅할 단독 박스 [fx, fy, "부호"] — fx/fy는 박스 중심의 이미지 폭·높이 대비 비율(0~1). 시각 판독 시 표시 좌표 ÷ 표시 크기로 추정
cyl 실린더(DB 등) — 내부 하단 중앙에 배치
container 최대 면적 박스(예: 제어부 컨테이너) 부호 — 내부 우상단
groups 점선 그룹: sym(대표 부호), members(멤버 박스 locator 좌표 — 검출 소진용, 무부호), tagged(예외적으로 부호 붙일 멤버 [idx, "부호"])
copy_only true면 무수정 복사 (부호가 이미 인쇄된 도면)

anchor는 대략적이어도 된다 — 스크립트가 검출 박스와 최근접 매칭하므로 박스 중심에서 다소 어긋나도 올바르게 붙는다. 박스가 밀집한 도면만 정확히.

Step 3. 실행

두 가지 스타일 엔진 중 선택:

# (a) 인라인 스타일 — 박스 내부 라벨 옆에 숫자
python scripts/tag_drawings.py --config <사건별 config.json>

# (b) KIPO 정식 작도 스타일 — 박스 외부 숫자 + 구불선 지시선 (레퍼런스: 사건 B 작도본)
python scripts/tag_drawings_leader.py --config <사건별 config.json>

leader 엔진(v2) config 확장: figure별 pad_top/left/right/bottom(캔버스 여백 확장 px), solo 항목 4번째 요소로 배치 방향(above/below/right/right_upper/left/above_left), groups에 "sides", tagged 항목 3번째 요소로 방향 지정. 1차 실행 리포트의 강제배치(False) 항목을 보고 pad·방향을 넣어 재실행하는 2-pass가 표준. 실전 config: 대학 고객 사건\사건 C_사건수임\도면부호태깅\config_leader.json

  • 출력: out_dir\도NN.png + 콘솔에 도면별 부호 수·문제 리포트
  • 한글 경로의 cv2 imread 실패 → 스크립트가 np.fromfile + imdecode로 처리 (내장됨)

Step 4. 전수 육안 검증 (필수)

태깅본 전부를 Read로 열어 (1) 부호가 올바른 박스에 붙었는지, (2) 라벨 텍스트와 겹치지 않는지 확인. 문제 도면만 anchor 수정 후 재실행. 검증 없이 납품 금지.

Step 5. 매핑표 산출

부호매핑표(md)를 작성하고 xlsx로 변환하여 태깅본과 같은 폴더에 저장: 구분(시스템/데이터/방법 단계) | 부호 | 명칭 | 등장 도면 | 관련 청구항.

배치 엔진 (스크립트 내장 규칙)

Read the full file on GitHub · 149 lines

Files

What ships with it

3 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. 11d ago First seen · 149 lines · 270 tokens per session scan A d8637145cd9d

Subscribe to this mod's changes

kr-patent-drawing-tagging is a skill published in the GitHub repository lsj4232/KR_PATENT_SKILL (14 stars, last pushed 18d ago), licensed MIT. It adds 270 tokens to every session and 3,001 once invoked, about $0.0014 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.

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