Agent skill · Audited from source

image-generation

skill · bytedance/deer-flowMIT licenceAudited 29 Oct 2026 · source 98f5f2c91674

★ 84,611pushed today
✓SAFEGrade B · 89/100 · 29 Oct 2026 · 98f5f2c
84,611repo stars · whole bytedance/deer-flow

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…

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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.

Trust audit

Audit 0.4.1 · source read 29 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium4 low0 info

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

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS4
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (4)

LOWObfuscation / stealthobf.decode_call · scripts/generate.py:201
F-07 Obfuscation / stealthCWE-506 · CWE-94Layer L1
f.write(base64.b64decode(images[0]))
Why
No further detail recorded for this rule.
Fix
—
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:245
F-07 Obfuscation / stealthCWE-506 · CWE-94Layer L1
f.write(base64.b64decode(base64_image))
Why
No further detail recorded for this rule.
Fix
—
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:258
F-07 Obfuscation / stealthCWE-506 · CWE-94Layer L1
image_bytes = base64.b64decode(encoded)
Why
No further detail recorded for this rule.
Fix
—
LOWObfuscation / stealthobf.decode_call · scripts/generate.py:267
F-07 Obfuscation / stealthCWE-506 · CWE-94Layer L1
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 c

Excerpt, 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

Download folder ↗
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

  1. ✓SAFE B 89 / 100

    first audit · source 98f5f2c91674

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/bytedance/image-generation/badge.svg)](https://modelsatlas.com/skills/bytedance/image-generation/)

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Add this badge to your README

[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/bytedance/image-generation/badge.svg)](https://modelsatlas.com/skills/bytedance/image-generation/)

Questions about image-generation

What does the image-generation skill do?
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
Is image-generation safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can image-generation access on my machine?
The audit observed that it reaches the network. Each of those is consistent with what it says it does. Secrets in the source: none found.
How current is this page?
The grade is for one exact copy of the source (98f5f2c91674), read on 2026-10-29. The repository is watched, and a new audit runs when it changes — this is the first audit.

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