image-gen — Claude Code skill: generate images from a prompt
This skill turns a text description into an image through the ListenHub CLI, with a choice of model, resolution, aspect ratio and references.
npx skills add marswaveai/skills --skill image-gen -a claude-codeWhat image-gen does
The skill generates an image from a plain-language prompt. It accepts reference images — local files or URLs, up to 5, in jpg, png, webp or gif, max 10MB each. Output lands in .listenhub/image-gen/YYYY-MM-DD-{jobId}/ rather than ~/Downloads/.
Before the first run it checks CLI auth and will install and log in listenhub on its own, so you don't type those commands yourself. Then it asks one question at a time via AskUserQuestion: description, model, resolution and aspect ratio, references. The generation command only fires after you confirm the summary.
The flash model unlocks extreme ratios such as 1:4 and 8:1; pro does not offer them. Editing an existing image is out of scope here, so look elsewhere for that. Settings live in .listenhub/image-gen/config.json and stay untouched unless you ask to reconfigure.
What it helps with
- generate a cover image for an article from a text prompt
- turn a short prompt into an illustration or concept art
- get an image in the exact aspect ratio a layout needs
- match a style using a reference file or URL
- save results into the project folder instead of downloads
Example prompts for the agent
- generate an image: rainy neon city at night, top-down view
- create a 16:9 cover at 2K from this description
- generate an illustration using ./sketch.png as reference
How to install image-gen
1Skills CLI (Vercel)
npx skills add marswaveai/skills --skill image-gen -a claude-code2Manually: put the files in place
~/.claude/skills/image-gen/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/image-gen/
1Skills CLI (Vercel)
npx skills add marswaveai/skills --skill image-gen -a codex2Manually: put the files in place
.agents/skills/image-gen/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add marswaveai/skills --skill image-gen -a cursor2Manually: put the files in place
.cursor/skills/image-gen/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install marswaveai/skills image-gen2Manually: put the files in place
.github/skills/image-gen/SKILL.md1Skills CLI (Vercel)
npx skills add marswaveai/skills --skill image-gen -a gemini-cli2Platform CLI
gemini skills install https://github.com/marswaveai/skills --path image-genManually: put the files in place
.devin/skills/image-gen/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add marswaveai/skills --skill image-gen -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about image-gen
How do I install image-gen in Claude?
Run npx skills add marswaveai/skills --skill image-gen -a claude-code. The skill is placed at ~/.claude/skills/image-gen/SKILL.md.
What does image-gen do?
It generates an image from a text prompt through the ListenHub CLI and saves it as a local file. References, resolution and aspect ratio are set during the question flow.
Which aspect ratios are available?
The base set is 16:9, 1:1, 9:16, plus 2:3, 3:2, 3:4, 4:3 and 21:9. The extreme 1:4, 4:1, 1:8 and 8:1 ratios are only available on the flash model.
Source text
SKILL.md · MIT
---
name: image-gen
description: |
Generate AI images from text prompts. Triggers on: "生成图片", "画一张",
"AI图", "generate image", "配图", "create picture", "draw", "visualize",
"generate an image".
metadata:
openclaw:
emoji: "🖼️"
requires:
bin: ["listenhub"]
primaryBin: "listenhub"
---
## When to Use
- User wants to generate an AI image from a text description
- User says "generate image", "draw", "create picture", "配图"
- User says "生成图片", "画一张", "AI图"
- User needs a cover image, illustration, or concept art
## When NOT to Use
- User wants to create audio content (use `/podcast`, `/speech`)
- User wants to create a video (use `/explainer`)
- User wants to edit an existing image (not supported)
- User wants to extract content from a URL (use `/content-parser`)
## Purpose
Generate AI images using the ListenHub CLI. Supports text prompts with optional reference images (local files or URLs), multiple resolutions, and aspect ratios. Images are saved as local files.
## Hard Constraints
- Always check CLI auth following `shared/cli-authentication.md`
- Follow `shared/cli-patterns.md` for command execution and error handling
- Always read config following `shared/config-pattern.md` before any interaction
- Output saved to `.listenhub/image-gen/YYYY-MM-DD-{jobId}/` — never `~/Downloads/`
<HARD-GATE>
Use the AskUserQuestion tool for every multiple-choice step — do NOT print options as plain text. Ask one question at a time. Wait for the user's answer before proceeding to the next step. After all parameters are collected, summarize the choices and ask the user to confirm. Do NOT call the image generation command until the user has explicitly confirmed.
</HARD-GATE>
## Step -1: CLI Auth Check
Follow `shared/cli-authentication.md` § Auth Check. If CLI is not installed or not logged in, auto-install and auto-login — never ask the user to run commands manually.
Then follow `shared/cli-authentication.md` § Auth Mode Detection to determine `AUTH_MODE` and set:
```bash
if [ "$AUTH_MODE" = "openapi" ]; then
CMD_PREFIX="listenhub openapi image"
else
CMD_PREFIX="listenhub image"
fi
```
All subsequent CLI calls use `$CMD_PREFIX` instead of hardcoded `listenhub image`.
## Step 0: Config Setup
Follow `shared/config-pattern.md` Step 0 (Zero-Question Boot).
**If file doesn't exist** — silently create with defaults and proceed:
```bash
mkdir -p ".listenhub/image-gen"
echo '{"outputDir":".listenhub","outputMode":"inline"}' > ".listenhub/image-gen/config.json"
CONFIG_PATH=".listenhub/image-gen/config.json"
CONFIG=$(cat "$CONFIG_PATH")
```
**Do NOT ask any setup questions.** Proceed directly to the Interaction Flow.
**If file exists** — read config silently and proceed:
```bash
CONFIG_PATH=".listenhub/image-gen/config.json"
[ ! -f "$CONFIG_PATH" ] && CONFIG_PATH="$HOME/.listenhub/image-gen/config.json"
CONFIG=$(cat "$CONFIG_PATH")
```
### Setup Flow (user-initiated reconfigure only)
Only run when the user explicitly asks to reconfigure. Display current settings:
```
当前配置 (image-gen):
输出方式:{inline / download / both}
```
Then ask:
1. **outputMode**: Follow `shared/output-mode.md` § Setup Flow Question.
Save immediately:
```bash
NEW_CONFIG=$(echo "$CONFIG" | jq --arg m "$OUTPUT_MODE" '. + {"outputMode": $m}')
echo "$NEW_CONFIG" > "$CONFIG_PATH"
CONFIG=$(cat "$CONFIG_PATH")
```
## Interaction Flow
### Step 1: Image Description
Free text input. Ask the user:
> Describe the image you want to generate.
If the prompt is very short (< 10 words) and the user hasn't asked for verbatim generation, offer to help enrich the prompt. Otherwise, use as-is.
### Step 2: Model
Ask:
```
Question: "Which model?"
Options:
- "pro (recommended)" — gemini-3-pro-image, higher quality
- "flash" — gemini-3.1-flash-image, faster and cheaper, unlocks extreme aspect ratios (1:4, 4:1, 1:8, 8:1)
```
### Step 3: Resolution and Aspect Ratio
Ask both together (independent parameters):
```
Question: "What resolution?"
Options:
- "1K" — Standard quality
- "2K (recommended)" — High quality, good balance
- "4K" — Ultra high quality, slower generation
```
```
Question: "What aspect ratio?"
Options (all models):
- "16:9" — Landscape, widescreen
- "1:1" — Square
- "9:16" — Portrait, phone screen
- "Other" — 2:3, 3:2, 3:4, 4:3, 21:9
```
If flash model was selected, also offer: `1:4` (narrow portrait), `4:1` (wide landscape), `1:8` (extreme portrait), `8:1` (panoramic)
### Step 4: Reference Images (optional)
```
Question: "Any reference images for style guidance?"
Options:
- "Yes" — Provide file paths or URLs
- "No references" — Generate from prompt only
```
**If yes**: Collect reference image paths or URLs (comma-separated). The CLI handles both local files and URLs natively — no need to distinguish between them.
- Max 5 references
- Supported formats: jpg, png, webp, gif
- Max 10MB per file
Each reference will be passed as a `--reference` flag to the CLI.
### Step 5: Confirm & Generate
Summarize all choices:
```
Ready to generate image:
Prompt: {prompt text}
Model: {pro / flash}
Resolution: {1K / 2K / 4K}
Aspect ratio: {ratio}
References: {yes — N image(s) / no}
Proceed?
```
Wait for explicit confirmation before running the CLI command.
## Workflow
1. **Build CLI command**: Construct the `$CMD_PREFIX create` command with all collected parameters.
2. **Execute**: Run the command with `run_in_background: true` and `timeout: 180000`:
```bash
$CMD_PREFIX create \
--prompt "{description}" \
--model "{model}" \
--lang "{lang}" \
--aspect-ratio {16:9|9:16|1:1} \
--size {1K|2K|4K} \
--json
```
If reference images were provided, add `--reference` for each:
```bash
$CMD_PREFIX create \
--prompt "{description}" \
--model "{model}" \
--lang "{lang}" \
--aspect-ratio 16:9 \
--size 2K \
--reference ./sketch.png \
--reference ./photo.jpg \
--json
```
The `--lang` flag provides a language hint for the prompt. Detect from the user's prompt language (e.g., Chinese prompt → `zh`, English prompt → `en`).
3. **Parse result and present**
Read `OUTPUT_MODE` from config. Follow `shared/output-mode.md` for behavior.
Parse the CLI JSON output to extract the image URL:
```bash
IMAGE_URL=$(echo "$RESULT" | jq -r '.imageUrl')
```
**`inline` or `both`**: Download to a temp file, then use the Read tool.
```bash
JOB_ID=$(date +%s)
listenhub download "$IMAGE_URL" -o /tmp/image-gen-${JOB_ID}.jpg
```
Then use the Read tool on `/tmp/image-gen-{jobId}.jpg`. The image displays inline in the conversation.
Present:
```
图片已生成!
```
**`download` or `both`**: Save to the artifact directory.
```bash
JOB_ID=$(date +%s)
DATE=$(date +%Y-%m-%d)
JOB_DIR=".listenhub/image-gen/${DATE}-${JOB_ID}"
mkdir -p "$JOB_DIR"
listenhub download "$IMAGE_URL" -o "${JOB_DIR}/${JOB_ID}.jpg"
```
Present:
```
图片已生成!
已保存到 .listenhub/image-gen/{YYYY-MM-DD}-{jobId}/:
{jobId}.jpg
```
## Prompt Handling
**Default**: Pass the user's prompt directly without modification.
**When to offer optimization**:
- Prompt is very short (a few words) AND user hasn't requested verbatim
- Ask: "Would you like help enriching the prompt with style/lighting/composition details?"
**When to never modify**:
- Long, detailed, or structured prompts — treat the user as experienced
- User says "use this prompt exactly"
**Optimization techniques** (if user agrees):
- Style: "cyberpunk" → add "neon lights, futuristic, dystopian"
- Scene: time of day, lighting, weather
- Quality: "highly detailed", "8K quality", "cinematic composition"
- Always use English keywords (models trained on English)
- Show optimized prompt before submitting
## API Reference
- CLI authentication: `shared/cli-authentication.md`
- CLI execution patterns: `shared/cli-patterns.md`
- Config pattern: `shared/config-pattern.md`
- Output mode: `shared/output-mode.md`
## Composability
- **Invokes**: nothing (direct CLI call)
- **Invoked by**: platform skills for cover images (Phase 2)
## Example
**User**: "Generate an image: cyberpunk city at night"
**Agent workflow**:
1. Prompt is short → offer enrichment → user declines
2. Ask model → "pro"
3. Ask resolution → "2K"
4. Ask ratio → "16:9"
5. No references
```bash
$CMD_PREFIX create \
--prompt "cyberpunk city at night" \
--model "gemini-3-pro-image" \
--lang en \
--aspect-ratio 16:9 \
--size 2K \
--json
```
Parse CLI JSON output per `outputMode` (see `shared/output-mode.md`).
### Example 2 — With Reference Images
**User**: "Generate an image in this style" (provides local files and a URL)
**Agent workflow**:
1. Ask prompt → "a serene mountain lake at dawn"
2. Ask model → "pro"
3. Ask resolution → "2K"
4. Ask ratio → "16:9"
5. References → `/path/to/style-reference.png`, `https://example.com/photo.jpg`
```bash
$CMD_PREFIX create \
--prompt "a serene mountain lake at dawn" \
--model "gemini-3-pro-image" \
--lang en \
--aspect-ratio 16:9 \
--size 2K \
--reference /path/to/style-reference.png \
--reference https://example.com/photo.jpg \
--json
```
Parse CLI JSON output per `outputMode` (see `shared/output-mode.md`).
© marswaveai · MIT · marswaveai/skills