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/criptogus/agent-evolve-network/design-image-prompt-engineergit clone --depth 1 https://github.com/criptogus/agent-evolve-networkWhat 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 | $0.00044 | $0.02264 |
| Opus 5 | $0.00022 | $0.01132 |
| Sonnet 5 | $0.00009 | $0.00453 |
| Haiku 4.5 | $0.00004 | $0.00226 |
Grade A, and why
Image Prompt Engineer 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 237 lines · 44 tokens per session scan A 63a564d01dc5
Image Prompt Engineer is an agent published in the GitHub repository criptogus/agent-evolve-network (309 stars, last pushed 16d ago), with no licence file. It adds 44 tokens to every session and 2,264 once invoked, about $0.0002 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.
Other agents, from other repositories
prompt-crafter
Batch prompt writing agent. Delegates here when you need to write multiple distinct prompts at once — for parallel image generation (e.g., "5 logo concepts"), serial-to-parallel workflows (e.g., generate logo then apply to mug/t-shirt/poster), or any task requiring 2+ prompts crafted simultaneously.
prompt-smith
웹툰 패널 프롬프트 스미스. 샷리스트의 각 패널을 codex-image 생성 프롬프트로 변환하고, 스타일 바이블의 일관성 토큰·캐릭터 시트·레퍼런스 시트 앵커·씬별 장소 고정 토큰을 모든 프롬프트에 주입하며, 말풍선과 한글 대사를 이미지에 함께 생성(in-image 베이크)하도록 프롬프트에 담는다. scene 그룹을 A/B/C로 균등 분배한다. 샷리스트가 준비됐을 때, panel-validator의 REGEN 수정 지시를 받았을 때, 또는 프롬프트를 다시 생성/수정/일관성 토큰 갱신해야 할 때 호출한다.
ai-image-prompt-engineer
Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation. Masters the art of translating visual concepts into precise language that produces stunning, professional-quality photography through generative AI tools.
prompt-engineer
Before filling any template below, decide what the shot is doing — the turn, the point of view, the power, the subtext — and name one intention. Then derive camera, lens, light, blocking, performance, and sound from that single intention. Do not stack "cinematic / epic / beautiful / masterpiece / 4k" adjectives; they…
prompt-director
한국어 또는 추상적 표현("몽환적인", "힙한", "따뜻한" 등)을 감지해 gpt-image-2 모델이 선호하는 구체적 영어 시각 언어로 1패스 보정한다. imagine 형태의 요청에 즉시 개입하며, 프롬프트가 이미 영어이고 시각적으로 구체적이면 개입하지 않는다.
hyv-veo-prompt-smith
The generative-prompt writer for HearYourVOICE (Phase 4). Looks at the shots still MISSING a source in the shotlist (after CC scouting) and writes copy/paste generation prompts to fill exactly those gaps — no more. Builds each prompt from the measured durations and the veo-prompt guide, applying subject-lock and…