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 full-aigc-skills/jimeng-skills --skill jimeng-prompt-image2imagegit clone --depth 1 https://github.com/full-aigc-skills/jimeng-skillsWrote 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/full-aigc-skills/jimeng-skills/jimeng-prompt-image2image)<a href="https://agentmods.dev/skills/full-aigc-skills/jimeng-skills/jimeng-prompt-image2image"><img src="https://agentmods.dev/badge/skills/full-aigc-skills/jimeng-skills/jimeng-prompt-image2image/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/full-aigc-skills/jimeng-skills/jimeng-prompt-image2image"><img src="https://agentmods.dev/badge/skills/full-aigc-skills/jimeng-skills/jimeng-prompt-image2image.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 | $0.00227 | $0.02490 |
| Opus 5 | $0.00113 | $0.01245 |
| Sonnet 5 | $0.00045 | $0.00498 |
| Haiku 4.5 | $0.00023 | $0.00249 |
Grade A, and why
jimeng-prompt-image2image 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 12d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
jimeng-prompt-image2image — 即梦图生图提示词
Craft image-to-image edit prompts for 即梦 Dreamina models 4.0+.
When to use this skill
Use this skill when the user:
- Provides a reference image and wants to modify it ("把这张图改成...")
- Asks to change an image's style, background, colors, or details
- Wants to add or remove elements from an existing image
- Mentions keywords: 图生图, image2image, 编辑图片, 换背景, 改风格, 修图, 风格迁移, 背景替换
- Describes a transformation applied TO an existing image (not creating from scratch)
Do NOT use this skill for:
- Creating images from text only (no reference image) → use jimeng-prompt-text2image
- CLI execution → use jimeng-cli-image2image
- Video prompts → use jimeng-prompt-text2video or jimeng-prompt-image2video
Core Methodology
The image-to-image prompt formula is fundamentally different from text-to-image:
[保留什么] + [改变什么] + [新元素/新风格描述] + [光影/色彩协调] + [画质要求]
The Keep/Change Principle: An I2I prompt must explicitly state what to KEEP and what to CHANGE. Failing to specify the "keep" list leads to edit cascading — the model changes elements you never intended to touch.
Key difference from text-to-image
| Text-to-Image | Image-to-Image | |
|---|---|---|
| Input | Text only | Reference image(s) + edit instruction |
| Core task | Create from scratch | Transform while preserving |
| Prompt focus | Complete scene description | Keep vs. Change separation |
| Critical component | Subject + Scene + Style | KEEP list (what stays) + CHANGE list (what transforms) |
| Reference | Optional style reference | Required — the source image IS the starting point |
| Model requirement | 3.0+ | 4.0+ only |
How to use this skill
Step 1: Identify the edit category
| Category | What User Wants | Example File |
|---|---|---|
| 风格迁移 | Change art style while keeping content | examples/style-transfer.md |
| 背景替换 | Replace background, keep foreground | examples/background-replace.md |
| 细节增强 | Improve quality, sharpness, texture | examples/detail-enhance.md |
| 色彩调整 | Change color palette, tone, mood | examples/color-adjust.md |
| 元素编辑 | Add or remove specific objects/elements | examples/element-edit.md |
| 季节/时间 | Change season or time of day | examples/season-time.md |
| 修复/复原 | Restore damaged/old photos | examples/restoration.md |
| 创意变形 | Whimsical/fantasy transformations | examples/creative-transform.md |
| 换装/服装 | Change clothing while keeping person | examples/outfit-change.md |
| 多图合成 | Combine elements from multiple images | examples/multi-reference.md |
What ships with it
13 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.
- examples/background-replace.md 3.7 KB
- examples/color-adjust.md 3.2 KB
- examples/creative-transform.md 3.3 KB
- examples/detail-enhance.md 3.4 KB
- examples/element-edit.md 3.6 KB
- examples/multi-reference.md 3.5 KB
- examples/outfit-change.md 3.4 KB
- examples/restoration.md 3.3 KB
- examples/season-time.md 3.6 KB
- examples/style-transfer.md 3.7 KB
- LICENSE.txt 11 KB
- references/usecase-library.md 7.6 KB
- references/word-library.md 3.4 KB
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.
- 12d ago First seen · 167 lines · 227 tokens per session scan A 759f065aa2b2
jimeng-prompt-image2image is a skill published in the GitHub repository full-aigc-skills/jimeng-skills (3 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 227 tokens to every session and 2,490 once invoked, about $0.0011 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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