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".

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: 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: Do NOT ask any setup questions. Proceed directly to the Interaction Flow. If file exists — read config silently and proceed: Setup Flow (user initiated reconfigure only) Only run when the user explicitly asks to reconfigure. Display current settings: Then ask: 1. outputMode : Follow shared/output mode.md § Setup Flow Question. Save immediately: 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: Step 3: Resolution and Aspect Ratio Ask both together (independent parameters): 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) 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: 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 : If reference images were provided, add reference for each: 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: inline or both : Download to a temp file, then use the Read tool. Then use the Read tool on /tmp/image gen {jobId}.jpg . The image displays inline in the conversation. Present: download or both : Save to the artifact directory. Present: 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 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 Parse CLI JSON output per outputMode (see shared/output mode.md ).

image-gen