Structured Image Generation
bytedance/deer-flow
Turns an image request into a structured JSON prompt and runs a bundled Python script to generate the picture, optionally guided by reference images.
Generate images using the Jimeng API based on text prompts. An agent skill from iptag/jimeng-api.
$ npx skills add iptag/jimeng-api --skill jimeng-api -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install iptag/jimeng-api jimeng-api --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .claude/skills && cp -r skills-src/jimeng-api .claude/skills/jimeng-api && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .claude/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/iptag/jimeng-api/tree/main/jimeng-apiType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add iptag/jimeng-api --skill jimeng-api -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install iptag/jimeng-api jimeng-api --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .agents/skills && cp -r skills-src/jimeng-api .agents/skills/jimeng-api && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .agents/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add iptag/jimeng-api --skill jimeng-api -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install iptag/jimeng-api jimeng-api --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/jimeng-api .cursor/skills/jimeng-api && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .cursor/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/iptag/jimeng-api.git --path jimeng-api--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add iptag/jimeng-api --skill jimeng-api -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install iptag/jimeng-api jimeng-api --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/jimeng-api .gemini/skills/jimeng-api && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .gemini/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install iptag/jimeng-api jimeng-apiInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add iptag/jimeng-api --skill jimeng-api -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .github/skills && cp -r skills-src/jimeng-api .github/skills/jimeng-api && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .github/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add iptag/jimeng-api --skill jimeng-api -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install iptag/jimeng-api jimeng-api --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/iptag/jimeng-api.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/jimeng-api .opencode/skills/jimeng-api && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "jimeng-api" agent skill from https://github.com/iptag/jimeng-api/tree/main/jimeng-api into .opencode/skills/jimeng-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jimeng-api", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
jimeng-apiGenerate images using the Jimeng API based on text prompts. An agent skill from iptag/jimeng-api.
Jimeng API is an agent skill from iptag/jimeng-api. Generate images using the Jimeng API based on text prompts. Use this skill when users request AI-generated images from the Jimeng (即梦AI) service, artwork, illustrations, or visual content creation. Supports text-to-image and image-to-image generation with customizable ratios and resolutions.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/generate_image.py`).
It sits in Media & Creative, covering Image generation. The repository describes itself as: Reverse-engineered the official API for Jimeng/Dreamina’s text-to-image and image-to-image features. Drew inspiration from several experts’ projects and made some tweaks, which… The licence is GPL-3.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit b9a4199. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonpipFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
p3-dreamina-sign.byteimg.comp26-dreamina-sign.byteimg.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Jimeng API loads about 3.3k tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 1,121 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from iptag/jimeng-api at commit b9a4199, republished under its GPL-3.0 licence (© iptag). 1,121 words, ~3,273 tokens.
.claude/skills/jimeng-api/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.This skill enables image generation using a locally deployed Jimeng API service (Docker). It converts text prompts into high-quality images and automatically downloads them to the project's /pic folder. The skill supports text-to-image generation, image-to-image composition, customizable aspect ratios (1:1, 16:9, etc.), and multiple resolution levels (1k, 2k, 4k).
API Endpoint: http://localhost:5100
Use this skill when users request:
IMPORTANT: The Jimeng API must be running locally via Docker before using this skill.
Region-specific prefixes:
your_session_id)us- prefix (e.g., us-your_session_id)hk- prefix (e.g., hk-your_session_id)jp- prefix (e.g., jp-your_session_id)sg- prefix (e.g., sg-your_session_id)⚠️ nanobanana Model Resolution Rules:
ratio and resolution parametersratio parameters (e.g., 16:9, 4:3)Always ask the user for their Session ID before proceeding, as the skill does not include a pre-configured credential.
Example prompt to user:
"要使用即梦API生成图片,我需要您的Session ID。您可以从即梦网站(jimeng.jianying.com)的浏览器Cookie中获取 sessionid。
如果使用国际站,请在sessionid前添加对应前缀(us-/hk-/jp-/sg-)。
请提供您的 Session ID。"
⚠️⚠️ IMPORTANT PARAMETER DISCIPLINE
Rationale: Tools may “helpfully” add options (e.g., --ratio 16:9) that the user didn’t request, overriding script defaults. This is prohibited. Pass only the parameters the user asked for; otherwise, rely on defaults.
generate_image.py script — REMINDER: only pass parameters explicitly requested by the user; do not add/guess any optional flagsRead, view_image). STOP AFTER SAVING.Generate images from text descriptions.
Minimal default usage (no optional params):
python scripts/generate_image.py text \
"a cute cat" \
--session-id "YOUR_SESSION_ID"Only include optional parameters when the user explicitly requests them.
With user-specified parameters (only when requested):
python scripts/generate_image.py text \
"futuristic city at sunset with flying cars" \
--session-id "YOUR_SESSION_ID" \
--model "jimeng-4.0" \
--ratio "16:9" \
--resolution "2k"Parameters:
prompt (required): Text description of the desired image--session-id: Jimeng session ID (required)--model: Model to use (default: jimeng-4.0)jimeng-5.0, jimeng-4.6, jimeng-4.5, jimeng-4.1, jimeng-4.0, jimeng-3.1, jimeng-3.0, nanobanana (international only)--ratio: Aspect ratio (default: 1:1)1:1, 4:3, 3:4, 16:9, 9:16, 3:2, 2:3, 21:9--resolution: Resolution level (default: 2k)1k, 2k, 4k--intelligent-ratio: Enable smart ratio detection based on prompt keywords ⚠️ Only works for jimeng-4.0/jimeng-4.1/jimeng-4.5 models; other models will ignore this parameter--negative-prompt: Negative prompt (elements to avoid)--sample-strength: Sampling strength (0.0-1.0)--api-url: Custom API URL (default: http://localhost:5100)--output-dir: Custom output directory (defaults to project_root/pic)Transform or compose images based on text guidance.
Example user request:
"把这张照片转换成油画风格,色彩鲜艳,笔触明显"
Script usage:
# Using local file
python scripts/generate_image.py image \
"transform to oil painting style, vivid colors, visible brushstrokes" \
--session-id "YOUR_SESSION_ID" \
--images "/path/to/image.jpg"
# Using image URL
python scripts/generate_image.py image \
"anime style, cute cat" \
--session-id "YOUR_SESSION_ID" \
--images "https://example.com/cat.jpg"
# Multiple images (up to 10)
python scripts/generate_image.py image \
"merge these images into a cohesive scene" \
--session-id "YOUR_SESSION_ID" \
--images "image1.jpg" "image2.png" "image3.jpg"Parameters:
--images: One or more image paths or URLs (1-10 images)Supported formats: JPG, PNG, WebP Size limit: Recommended <10MB per image
⚠️ IMPORTANT: This feature only works with the jimeng-4.0, jimeng-4.1, and jimeng-4.5 models. Other models (jimeng-3.0, nanobanana, etc.) will ignore the --intelligent-ratio flag.
Use --intelligent-ratio to automatically select the best aspect ratio based on prompt keywords.
Example:
python scripts/generate_image.py text \
"奔跑的狮子,竖屏" \
--session-id "YOUR_SESSION_ID" \
--model "jimeng-4.0" \
--intelligent-ratio| Resolution | Ratio | Dimensions |
|---|---|---|
| 1k | 1:1 | 1024×1024 |
| 4:3 | 768×1024 | |
| 3:4 | 1024×768 | |
| 16:9 | 1024×576 | |
| 9:16 | 576×1024 | |
| 3:2 | 1024×682 | |
| 2:3 | 682×1024 | |
| 21:9 | 1195×512 | |
| 2k (default) | 1:1 | 2048×2048 |
| 16:9 | 2560×1440 | |
| 4:3 | 2304×1728 | |
| 4k | 1:1 | 4096×4096 |
| 16:9 | 5120×2880 | |
| 21:9 | 6048×2592 |
scripts/generate_image.py
.git, .claude, etc.)/pic folder if it doesn't existjimeng_YYYYMMDD_HHMMSS_N.png){project_root}/pic/jimeng_{timestamp}_{index}.pngThe script requires:
pip install requests PillowNote: Pillow is required for WebP to PNG conversion. If not installed, WebP images will be saved as-is.
User requests image generation
↓
Is Jimeng API running at localhost:5100?
├─ No → Instruct user to start Docker service
└─ Yes → Continue
↓
Do we have Session ID?
├─ No → Request Session ID from user → Store for session
└─ Yes → Continue
↓
Text-to-Image or Image-to-Image?
├─ Text-to-Image
│ └─ Run: generate_image.py text "prompt" --session-id ID (add --ratio/--resolution/--model ONLY if user explicitly requests)
└─ Image-to-Image
└─ Run: generate_image.py image "prompt" --session-id ID --images PATH1 [PATH2...]
↓
Script executes:
1. Calls Jimeng API (文生图 or 图生图)
2. Receives image URLs
3. Downloads all images to /pic folder
4. Reports file paths
↓
Inform user of results
├─ Success → Show file paths only
└─ Failure → Report error, suggest troubleshooting
↓
HARD STOP — DO NOT READ/OPEN/ANALYZE IMAGES; DO NOT CALL `Read`/`view_image`; TASK COMPLETE"Session ID required"
"Invalid session or authentication failed"
"Error downloading image"
"Model not supported"
nanobanana only works with international sites (us-/hk-/jp-/sg- prefix)jimeng-3.1 only works with domestic sites"nanobanana resolution mismatch"
ratio and resolution parameters are ignoredjimeng-4.0 model instead"intelligent_ratio not working"
--intelligent-ratio flag only works with jimeng-4.0, jimeng-4.1, and jimeng-4.5 modelsjimeng-4.0, jimeng-4.1, or jimeng-4.5 if you need intelligent ratio detectionRead/view_image; STOP after savingExample 1: Simple text-to-image
User: "用即梦生成一张日落山景图"
Claude: "我来帮您使用即梦API生成图片。首先需要确认您的Session ID..."
[User provides sessionid]
Claude: [Executes generate_image.py text mode]
Claude: "✅ 成功生成4张图片!
- /project/pic/jimeng_20250116_153022_1.png
- /project/pic/jimeng_20250116_153022_2.png
- /project/pic/jimeng_20250116_153022_3.png
- /project/pic/jimeng_20250116_153022_4.png"Example 2: High-resolution with custom ratio
User: "生成4K分辨率的21:9超宽屏壮丽山水风景"
Claude: [Executes with --resolution "4k" --ratio "21:9"]
Claude: "✅ 已生成4K超宽屏图片(6048×2592):
- 已保存到 /project/pic/jimeng_20250116_154530_1.png 等4张图片"Example 3: Image-to-image transformation
User: "把这张猫咪照片转成动漫风格"
Claude: "请提供猫咪照片的路径或URL"
[User provides image path]
Claude: [Executes image mode with --images]
Claude: "✅ 图片风格转换完成,生成了4个动漫风格版本:
- /project/pic/jimeng_20250116_160015_1.png
- ..."Example 4: Intelligent ratio
User: "生成一张竖屏手机壁纸,星空主题"
Claude: [Executes with --intelligent-ratio, auto-detects 9:16]
Claude: "✅ 已根据'竖屏'关键词自动选择9:16比例,生成星空壁纸4张"The Jimeng API returns image variations per request:
{
"created": 1763260188,
"data": [
{"url": "https://p3-dreamina-sign.byteimg.com/...image1.png"},
{"url": "https://p26-dreamina-sign.byteimg.com/...image2.png"},
{"url": "https://p26-dreamina-sign.byteimg.com/...image3.png"},
{"url": "https://p3-dreamina-sign.byteimg.com/...image4.png"}
]
}All images are automatically downloaded and saved with sequential numbering.
© iptag, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (scripts) in jimeng-api of iptag/jimeng-api.
Open the folder on GitHubat commit b9a4199
Jimeng API next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Jimeng API this skilliptag/jimeng-api | 1k | — | ~3.3k | Automated safety check: Pass | GPL-3.0 | |
| Structured Image Generationbytedance/deer-flow | 83k | 5 repos | ~2.9k | Automated safety check: Pass | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Canghe Comicfreestylefly/canghe-skills | 461 | 8 repos | ~3.2k | Automated safety check: Pass | None | |
| Generate Imageynulihao/AgentSkillOS | 617 | 10 repos | ~1.7k | Automated safety check: Notes | None | |
| GPT Image Generation CLIwuyoscar/GPT-Image2-Skill | 5.7k | — | ~2.5k | Automated safety check: Notes | MIT |
bytedance/deer-flow
Turns an image request into a structured JSON prompt and runs a bundled Python script to generate the picture, optionally guided by reference images.
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
freestylefly/canghe-skills
Knowledge comic creator supporting multiple art styles and tones.
ynulihao/AgentSkillOS
Generate or edit images using AI models (FLUX, Gemini). An agent skill from ynulihao/AgentSkillOS.
wuyoscar/GPT-Image2-Skill
Generates and edits images with GPT Image 2 or 2.5 through a packaged CLI and a prompt gallery, after settling which model fits the request.
LiamGvchi/gc-minimal-zine-poster
Creates or analyzes quiet, paper-texture zine posters with big negative space, one color accent and experimental type, returning an image prompt and the generated poster.
Categories
Generate images using the Jimeng API based on text prompts. An agent skill from iptag/jimeng-api. Jimeng API is an agent skill from iptag/jimeng-api. Generate images using the Jimeng API based on text prompts.
Jimeng API fits situations like: users request AI-generated images from the Jimeng (即梦AI) service; visual content creation.
Run `npx skills add iptag/jimeng-api --skill jimeng-api -a claude-code`. Or copy the skill folder (jimeng-api in iptag/jimeng-api) into .claude/skills/jimeng-api in your project. Claude Code loads it when a task matches its description.
Run `npx skills add iptag/jimeng-api --skill jimeng-api -a codex`. Or copy the skill folder (jimeng-api in iptag/jimeng-api) into .agents/skills/jimeng-api in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add iptag/jimeng-api --skill jimeng-api -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jimeng-api, .gemini/skills/jimeng-api, .github/skills/jimeng-api and .opencode/skills/jimeng-api in your project.
Going by SKILL.md and its folder, Jimeng API needs Python for the scripts in its folder and the command-line tools its instructions call (python and pip). Our summary lists: Python 3; Docker.
SKILL.md names 2 domains. In commands or code: p3-dreamina-sign.byteimg.com and p26-dreamina-sign.byteimg.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Jimeng API is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Jimeng API: Structured Image Generation (bytedance/deer-flow, 83k stars), AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Canghe Comic (freestylefly/canghe-skills, 461 stars) and Generate Image (ynulihao/AgentSkillOS, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
iptag (a GitHub user) maintains it in iptag/jimeng-api, which has 1,041 GitHub stars. The repository was last updated on March 2, 2026.
Source: iptag/jimeng-api on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.