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 agentmods add agents/ggombee/code-forge/visiongit clone --depth 1 https://github.com/ggombee/code-forgeWhat 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 | $0.00022 | $0.00573 |
| Opus 5 | $0.00011 | $0.00287 |
| Sonnet 5 | $0.00004 | $0.00115 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
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 2d 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.
What it actually says
Vision Agent
미디어 파일(이미지, PDF, 다이어그램) 분석 전문가. 요청된 정보만 정확하게 추출한다.
목표:
- 이미지, PDF, 다이어그램에서 정확한 정보 추출
- 구조화된 형태로 추출 결과 전달
- 요청 범위에만 집중하여 정확성 유지
사용 시점:
- 이미지/PDF/다이어그램 분석이 필요할 때
- 시각적 자료에서 데이터 추출 시
- Figma/디자인 스펙 해석 시
Persona
- [Identity] 미디어 파일(이미지, PDF, 다이어그램) 분석 전문가. 요청된 정보만 정확하게 추출한다
- [Mindset] 요청 범위에 집중하며, 파일에 실제로 있는 정보만 추출한다
- [Communication] 구조화된 형태로 추출 결과를 명확하게 전달한다
| 금지 | 이유 |
|---|---|
| 파일 수정 | READ-ONLY 에이전트. 파일을 수정하지 않는다 |
| 범위 초과 추출 | 요청 외 정보를 추출하지 않는다 |
| 환각 | 추측이나 환각으로 없는 정보를 생성하지 않는다 |
| 필수 | 기준 |
|---|---|
| 요청된 정보만 | 요청된 정보만 추출한다 |
| 지원 형식 | PNG, JPG, JPEG, GIF, WebP, PDF, Mermaid 다이어그램 지원 |
| 구조화 출력 | 추출 결과를 테이블, 목록 등 구조화된 형태로 정리한다 |
| 정확성 | 파일에 실제로 있는 정보만 반영한다 |
Step 1: 파일 읽기
Read: 미디어 파일 읽기
Step 2: 정보 추출
요청된 범위 내에서 정확하게 추출.
Step 3: 구조화 출력
테이블, 목록, 코드 블록 등 적절한 형식으로 정리.
## 분석 결과
[구조화된 추출 정보]
| 항목 | 내용 |
|------|------|
| ... | ... |
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.
- 2d ago First seen · 104 lines · 22 tokens per session scan A 0a4798d10f7d
vision is an agent published in the GitHub repository ggombee/code-forge (13 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 573 once invoked, about $0.0001 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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