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.
npx skills add joonlab/joonlab-claudecode-setting-for-share --skill gemini-agentic-visiongit clone --depth 1 https://github.com/joonlab/joonlab-claudecode-setting-for-shareWrote 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.
[](https://agentmods.dev/skills/joonlab/joonlab-claudecode-setting-for-share/gemini-agentic-vision)<a href="https://agentmods.dev/skills/joonlab/joonlab-claudecode-setting-for-share/gemini-agentic-vision"><img src="https://agentmods.dev/badge/skills/joonlab/joonlab-claudecode-setting-for-share/gemini-agentic-vision/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.
<a href="https://agentmods.dev/skills/joonlab/joonlab-claudecode-setting-for-share/gemini-agentic-vision"><img src="https://agentmods.dev/badge/skills/joonlab/joonlab-claudecode-setting-for-share/gemini-agentic-vision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00173 | $0.01383 |
| Opus 5 | $0.00086 | $0.00691 |
| Sonnet 5 | $0.00035 | $0.00277 |
| Haiku 4.5 | $0.00017 | $0.00138 |
Grade A, and why
gemini-agentic-vision 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.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini Agentic Vision
Gemini API의 Vision + Extended Thinking + Code Execution을 조합하여, 이미지를 입력받고 자율적으로 분석→코드 작성→실행→결과물 생성을 수행하는 스킬.
환경 요구사항
- Python 패키지:
google-genai(설치됨) - API 키:
GEMINI_PAID_API_KEY환경변수 (.zshrc에 설정됨) - 모델:
gemini-3-flash-preview
사용법
기본 실행
source ~/.zshrc && python3 ~/.claude/skills/gemini-agentic-vision/scripts/gemini_vision.py \
"<이미지_경로>" \
"<프롬프트>"
출력 디렉토리 지정
source ~/.zshrc && python3 ~/.claude/skills/gemini-agentic-vision/scripts/gemini_vision.py \
"<이미지_경로>" \
"<프롬프트>" \
--output-dir "<출력_디렉토리>"
생성된 코드 저장
source ~/.zshrc && python3 ~/.claude/skills/gemini-agentic-vision/scripts/gemini_vision.py \
"<이미지_경로>" \
"<프롬프트>" \
--save-code "/tmp/generated.py"
JSON 결과 출력 (파싱용)
source ~/.zshrc && python3 ~/.claude/skills/gemini-agentic-vision/scripts/gemini_vision.py \
"<이미지_경로>" \
"<프롬프트>" \
--json
중요: 반드시 source ~/.zshrc &&를 앞에 붙여 GEMINI_PAID_API_KEY 환경변수를 로드한다.
워크플로우
Phase 1: 프롬프트 구성
사용자의 요청을 Gemini에 최적화된 프롬프트로 변환한다:
| 사용자 요청 | 최적 프롬프트 |
|---|---|
| "동물만 잘라내줘" | "Detect all animals, crop each one, and save as separate images" |
| "데이터 추출해줘" | "Extract all data from this chart and output as CSV" |
| "빨간 박스로 표시해줘" | "Draw red bounding boxes around all buttons and save the annotated image" |
| "개수 세줘" | "Count all items, number each one on the image, and report total" |
| "비교해줘" | "Analyze this image and describe key visual elements in detail" |
프롬프트는 영어로 작성하면 Gemini의 코드 실행 정확도가 높아진다.
Phase 2: 스크립트 실행
scripts/gemini_vision.py를 Bash로 실행한다. 스크립트가 자동으로:
- 이미지를 base64로 인코딩하여 Gemini API에 전달
- Gemini가 이미지를 분석하고 사고 과정(Thinking)을 노출
- 필요시 Python 코드를 자율 생성하고 서버에서 실행
- 실행 결과(텍스트, 이미지, 데이터)를 반환
Phase 3: 결과 확인
스크립트 출력에서:
🖼️ [Output Image]뒤의 경로 → 생성된 이미지 파일📝뒤의 텍스트 → Gemini의 분석 결과💻 [Code]→ 실행된 코드 (참고/재사용 가능)✅ [Result]→ 코드 실행 출력
출력된 이미지 파일은 Read 도구로 사용자에게 보여준다.
Phase 4: 후속 처리
Gemini 결과를 바탕으로 추가 작업이 필요하면:
- 생성된 코드를 로컬에서 수정·재실행
- 출력 이미지를 추가 가공
- 추출된 데이터를 다른 형식으로 변환
What ships with it
1 file 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.
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.
- 9d ago First seen · 141 lines · 173 tokens per session scan A 258293542c20
gemini-agentic-vision is a skill published in the GitHub repository joonlab/joonlab-claudecode-setting-for-share (10 stars, last pushed 1mo ago), licensed MIT. It adds 173 tokens to every session and 1,383 once invoked, about $0.0009 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 2026-08-31.
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