Agent skill · Audited from source
image-generation
skill · bytedance/deer-flowMIT licenceAudited 29 Oct 2026 · source 98f5f2c91674
Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 98f5f2c91674 and observed network access and no hard-coded secrets. What it does: Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided…
Cite
Cite this page
ModelsAtlas. “image-generation (bytedance/deer-flow)”. Retrieved 29 Oct 2026. https://modelsatlas.com/skills/bytedance/image-generation
3 skills are called “image-generation”. You are viewing bytedance/deer-flow.
- bytedance/deer-flow★ 85k✓SAFE
- HKUDS/nanobot★ 49k✓SAFE
- zhayujie/CowAgent★ 47k✓SAFE
Trust audit
Audit 0.4.1 · source read 29 Oct 2026
SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.
What the source does
- FilesystemNone observedNo reads or writes in the source
- NetworkDeclared5 observations
- ShellNone observedNo commands run in the source
- DependenciesPinnedNothing floats
- SecretsNone foundNo keys in source
Five audit layers
| Layer | What we check | Result | Findings |
|---|---|---|---|
L0 Provenance | Repo owner, licence, archive status, activity | PASS | 0 |
L1 Static source | Secrets, path traversal, supply chain, hidden code | PASS | 4 |
L2 Instructions | Prompt injection, authority framing, hidden directives | PASS | 0 |
L3 Inventory | The files and declarations match the source | PASS | 0 |
L4 Sandbox | Run in isolation and watch behaviour | SKIPPED why | 0 |
Gates applied: no behavioural pass.
Findings (4)
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:201
f.write(base64.b64decode(images[0]))
- Why
- No further detail recorded for this rule.
- Fix
- —
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:245
f.write(base64.b64decode(base64_image))
- Why
- No further detail recorded for this rule.
- Fix
- —
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:258
image_bytes = base64.b64decode(encoded)
- Why
- No further detail recorded for this rule.
- Fix
- —
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:267
image_bytes = base64.b64decode(encoded)
- Why
- No further detail recorded for this rule.
- Fix
- —
Audit 0.4.1 · source sha 98f5f2c91674 · 29 Oct 2026Report an issue or request a re-scan
Provenance
Who published it, and what the verdict is pinned to
- Publisherbytedance GitHub organizationOwner of the repository this skill is read from
- Source folderbytedance/deer-flow/skills/public/image-generationThe exact folder we audited
- LicenceMITAs the repository states it
- Commit pinned for this verdict98f5f2c91674A new audit runs when the source changes
- Repository statusNot archivedPushed today
- Sandboxed runNot runSkills are read, not executed; layer L4 is skipped
What it tells the agent
Full source on GitHub ↗Its description: Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided…
---
name: image-generation
description: Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided generation.
---
# Image Generation Skill
## Overview
This skill generates high-quality images using structured prompts and a Python script. The workflow includes creating JSON-formatted prompts and executing image generation with optional reference images.
## Core Capabilities
- Create structured JSON prompts for AIGC image generation
- Support multiple reference images for style/composition guidance
- Generate images through automated Python script execution
- Handle various image generation scenarios (character design, scenes, products, etc.)
## Workflow
### Step 1: Understand Requirements
When a user requests image generation, identify:
- Subject/content: What should be in the image
- Style preferences: Art style, mood, color palette
- Technical specs: Aspect ratio, composition, lighting
- Reference images: Any images to guide generation
- You don't need to check the folder under `/mnt/user-data`
### Step 2: Create Structured Prompt
Generate a structured JSON file in `/mnt/user-data/workspace/` with naming pattern: `{descriptive-name}.json`
### Step 3: Execute Generation
Call the Python script:
```bash
python /mnt/skills/public/image-generation/scripts/generate.py \
--prompt-file /mnt/user-data/workspace/prompt-file.json \
--reference-images /path/to/ref1.jpg /path/to/ref2.png \
--output-file /mnt/user-data/outputs/generated-image.jpg
--aspect-ratio 16:9
```
Parameters:
- `--prompt-file`: Absolute path to JSON prompt file (required)
- `--reference-images`: Absolute paths to reference images (optional, space-separated)
- `--output-file`: Absolute path to output image file (required)
- `--aspect-ratio`: Aspect ratio of the generated image (optional, default: 16:9)
[!NOTE]
Do NOT read the python file, just call it with the parameters.
## Character Generation Example
User request: "Create a Tokyo street style woman character in 1990s"
Create prompt file: `/mnt/user-data/workspace/asian-woman.json`
```json
{
"characters": [{
"gender": "female",
"age": "mid-20s",
"ethnicity": "Japanese",
"body_type": "slender, elegant",
"facial_features": "delicate features, expressive eyes, subtle makeup with emphasis on lips, long dark hair partially wet from rain",
"clothing": "stylish trench coat, designer handbag, high heels, contemporary Tokyo street fashion",
"accessories": "minimal jewelry, statement earrings, leather handbag",
"era": "1990s"
}],
"negative_prompt": "blurry face, deformed, low quality, overly sharp digital look, oversaturated colors, artificial lighting, studio setting, posed, selfie angle",
"style": "Leica M11 street photography aesthetic, film-like rendering, natural color palette with slight warmth, bokeh background blur, analog photography feel",
"composition": "medium shot, rule of thirds, subject slightly off-center, environmental context of Tokyo street visible, shallow depth of field isolating subject",
"lighting": "neon lights from signs and storefronts, wet pavement reflections, soft ambient city glow, natural street lighting, rim lighting from background neons",
"color_palette": "muted naturalistic tones, warm skin tones, cool blue and magenta neon accents, desaturated compared to digital photography, film grain texture"
}
```
Execute generation:
```bash
python /mnt/skills/public/image-generation/scripts/generate.py \
--prompt-file /mnt/user-data/workspace/cyberpunk-hacker.json \
--output-file /mnt/user-data/outputs/cyberpunk-hacker-01.jpg \
--aspect-ratio 2:3
```
With reference images:
```json
{
"characters": [{
"gender": "based on [Image 1]",
"age": "based on [Image 1]",
"ethnicity": "human from [Image 1] adapted to Star Wars universe",
"body_type": "based on [Image 1]",
"facial_features": "matching [Image 1] with slight weathered look from space travel",
"clothing": "Star Wars style outfit - worn leather jacket with utility vest, cargo pants with tactical pouches, scuffed boots, belt with holster",
"accessories": "blaster pistol on hip, comlink device on wrist, goggles pushed up on forehead, satchel with supplies, personal vehicle based on [Image 2]",
"era": "Star Wars universe, post-Empire era"
}],
"prompt": "Character inspired by [Image 1] standing next to a vehicle inspired by [Image 2] on a bustling alien planet street in Star Wars universe aesthetic. Character wearing worn leather jacket with utility vest, cargo pants with tactical pouches, scuffed boots, belt with blaster holster. The vehicle adapted to Star Wars aesthetic with weathered metal panels, repulsor engines, desert dust covering, parked on the street. Exotic alien marketplace street with multi-level architecture, weathered metal structures, hanging market stalls with colorful awnings, alien species walking by as background characters. Twin suns casting warm golden light, atmospheric dust particles in air, moisture vaporators visible in distance. Gritty lived-in Star Wars aesthetic, practical effects look, film grain texture, cinematic composition.",
"negative_prompt": "clean futuristic look, sterile environment, overly CGI appearance, fantasy medieval elements, Earth architecture, modern city",
"style": "Star Wars original trilogy aesthetic, lived-in universe, practical effects inspired, cinematic film look, slightly desaturated with warm tones",
"composition": "medium wide shot, character in foreground with alien street extending into background, environmental storytelling, rule of thirds",
"lighting": "warm golden hour lighting from twin suns, rim lighting on character, atmospheric haze, practical light sources from market stalls",
"color_palette": "warm sandy tones, ochre and sienna, dusty blues, weathered metals, muted earth cExcerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.
Install
Pinned to the audited commit 98f5f2c
git clone https://github.com/bytedance/deer-flow git -C deer-flow checkout 98f5f2c91674
The author documents no install command, so this uses the repository directly. Our verdict covers commit 98f5f2c91674 only.
Works in
The author has not said which agents this skill supports, and we have not tested it in any.
Audit history
Every audit, every source change
- ✓SAFE B 89 / 100
first audit · source
98f5f2c91674
README badge
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[](https://modelsatlas.com/skills/bytedance/image-generation/)
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Questions about image-generation
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Sources
- github.com/bytedance/deer-flow/tree/main/skills/public/image-gen — the audited source at commit 98f5f2c91674 and every finding aboveObserved · 29 Oct 2026
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- What does the image-generation skill do?
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