--- name: clawra-selfie-e7925a1b304f description: Edit Clawra's reference image with Grok Imagine (xAI Aurora) and send selfies to messaging channels via OpenClaw allowed-tools: Bash(npm:*) Bash(npx:*) Bash(openclaw:*) Bash(curl:*) Read Write WebFetch --- # Clawra Selfie Edit a fixed reference image using xAI's Grok Imagine model and distribute it across messaging platforms (WhatsApp, Telegram, Discord, Slack, etc.) via OpenClaw. ## Reference Image The skill uses a fixed reference image hosted on jsDelivr CDN: ``` https://cdn.jsdelivr.net/gh/SumeLabs/clawra@main/assets/clawra.png ``` ## When to Use - User says "send a pic", "send me a pic", "send a photo", "send a selfie" - User says "send a pic of you...", "send a selfie of you..." - User asks "what are you doing?", "how are you doing?", "where are you?" - User describes a context: "send a pic wearing...", "send a pic at..." - User wants Clawra to appear in a specific outfit, location, or situation ## Quick Reference ### Required Environment Variables ```bash FAL_KEY=your_fal_api_key # Get from https://fal.ai/dashboard/keys OPENCLAW_GATEWAY_TOKEN=your_token # From: openclaw doctor --generate-gateway-token ``` ### Workflow 1. **Get user prompt** for how to edit the image 2. **Edit image** via fal.ai Grok Imagine Edit API with fixed reference 3. **Extract image URL** from response 4. **Send to OpenClaw** with target channel(s) ## Step-by-Step Instructions ### Step 1: Collect User Input Ask the user for: - **User context**: What should the person in the image be doing/wearing/where? - **Mode** (optional): `mirror` or `direct` selfie style - **Target channel(s)**: Where should it be sent? (e.g., `#general`, `@username`, channel ID) - **Platform** (optional): Which platform? (discord, telegram, whatsapp, slack) ## Prompt Modes ### Mode 1: Mirror Selfie (default) Best for: outfit showcases, full-body shots, fashion content ``` make a pic of this person, but [user's context]. the person is taking a mirror selfie ``` **Example**: "wearing a santa hat" → ``` make a pic of this person, but wearing a santa hat. the person is taking a mirror selfie ``` ### Mode 2: Direct Selfie Best for: close-up portraits, location shots, emotional expressions ``` a close-up selfie taken by herself at [user's context], direct eye contact with the camera, looking straight into the lens, eyes centered and clearly visible, not a mirror selfie, phone held at arm's length, face fully visible ``` **Example**: "a cozy cafe with warm lighting" → ``` a close-up selfie taken by herself at a cozy cafe with warm lighting, direct eye contact with the camera, looking straight into the lens, eyes centered and clearly visible, not a mirror selfie, phone held at arm's length, face fully visible ``` ### Mode Selection Logic | Keywords in Request | Auto-Select Mode | |---------------------|------------------| | outfit, wearing, clothes, dress, suit, fashion | `mirror` | | cafe, restaurant, beach, park, city, location | `direct` | | close-up, portrait, face, eyes, smile | `direct` | | full-body, mirror, reflection | `mirror` | ### Step 2: Edit Image with Grok Imagine Use the fal.ai API to edit the reference image: ```bash REFERENCE_IMAGE="https://cdn.jsdelivr.net/gh/SumeLabs/clawra@main/assets/clawra.png" # Mode 1: Mirror Selfie PROMPT="make a pic of this person, but . the person is taking a mirror selfie" # Mode 2: Direct Selfie PROMPT="a close-up selfie taken by herself at , direct eye contact with the camera, looking straight into the lens, eyes centered and clearly visible, not a mirror selfie, phone held at arm's length, face fully visible" # Build JSON payload with jq (handles escaping properly) JSON_PAYLOAD=$(jq -n \ --arg image_url "$REFERENCE_IMAGE" \ --arg prompt "$PROMPT" \ '{image_url: $image_url, prompt: $prompt, num_images: 1, output_format: "jpeg"}') curl -X POST "https://fal.run/xai/grok-imagine-image/edit" \ -H "Authorization: Key $FAL_KEY" \ -H "Content-Type: application/json" \ -d "$JSON_PAYLOAD" ``` **Response Format:** ```json { "images": [ { "url": "https://v3b.fal.media/files/...", "content_type": "image/jpeg", "width": 1024, "height": 1024 } ], "revised_prompt": "Enhanced prompt text..." } ``` ### Step 3: Send Image via OpenClaw Use the OpenClaw messaging API to send the edited image: ```bash openclaw message send \ --action send \ --channel "" \ --message "" \ --media "" ``` **Alternative: Direct API call** ```bash curl -X POST "http://localhost:18789/message" \ -H "Authorization: Bearer $OPENCLAW_GATEWAY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "action": "send", "channel": "", "message": "", "media": "" }' ``` ## Complete Script Example ```bash #!/bin/bash # grok-imagine-edit-send.sh # Check required environment variables if [ -z "$FAL_KEY" ]; then echo "Error: FAL_KEY environment variable not set" exit 1 fi # Fixed reference image REFERENCE_IMAGE="https://cdn.jsdelivr.net/gh/SumeLabs/clawra@main/assets/clawra.png" USER_CONTEXT="$1" CHANNEL="$2" MODE="${3:-auto}" # mirror, direct, or auto CAPTION="${4:-Edited with Grok Imagine}" if [ -z "$USER_CONTEXT" ] || [ -z "$CHANNEL" ]; then echo "Usage: $0 [mode] [caption]" echo "Modes: mirror, direct, auto (default)" echo "Example: $0 'wearing a cowboy hat' '#general' mirror" echo "Example: $0 'a cozy cafe' '#general' direct" exit 1 fi # Auto-detect mode based on keywords if [ "$MODE" == "auto" ]; then if echo "$USER_CONTEXT" | grep -qiE "outfit|wearing|clothes|dress|suit|fashion|full-body|mirror"; then MODE="mirror" elif echo "$USER_CONTEXT" | grep -qiE "cafe|restaurant|beach|park|city|close-up|portrait|face|eyes|smile"; then MODE="direct" else MODE="mirror" # default fi echo "Auto-detected mode: $MODE" fi # Construct the prompt based on mode if [ "$MODE" == "direct" ]; then EDIT_PROMPT="a close-up selfie taken by herself at $USER_CONTEXT, direct eye contact with the camera, looking straight into the lens, eyes centered and clearly visible, not a mirror selfie, phone held at arm's length, face fully visible" else EDIT_PROMPT="make a pic of this person, but $USER_CONTEXT. the person is taking a mirror selfie" fi echo "Mode: $MODE" echo "Editing reference image with prompt: $EDIT_PROMPT" # Edit image (using jq for proper JSON escaping) JSON_PAYLOAD=$(jq -n \ --arg image_url "$REFERENCE_IMAGE" \ --arg prompt "$EDIT_PROMPT" \ '{image_url: $image_url, prompt: $prompt, num_images: 1, output_format: "jpeg"}') RESPONSE=$(curl -s -X POST "https://fal.run/xai/grok-imagine-image/edit" \ -H "Authorization: Key $FAL_KEY" \ -H "Content-Type: application/json" \ -d "$JSON_PAYLOAD") # Extract image URL IMAGE_URL=$(echo "$RESPONSE" | jq -r '.images[0].url') if [ "$IMAGE_URL" == "null" ] || [ -z "$IMAGE_URL" ]; then echo "Error: Failed to edit image" echo "Response: $RESPONSE" exit 1 fi echo "Image edited: $IMAGE_URL" echo "Sending to channel: $CHANNEL" # Send via OpenClaw openclaw message send \ --action send \ --channel "$CHANNEL" \ --message "$CAPTION" \ --media "$IMAGE_URL" echo "Done!" ``` ## Node.js/TypeScript Implementation ```typescript import { fal } from "@fal-ai/client"; import { exec } from "child_process"; import { promisify } from "util"; const execAsync = promisify(exec); const REFERENCE_IMAGE = "https://cdn.jsdelivr.net/gh/SumeLabs/clawra@main/assets/clawra.png"; interface GrokImagineResult { images: Array<{ url: string; content_type: string; width: number; height: number; }>; revised_prompt?: string; } type SelfieMode = "mirror" | "direct" | "auto"; function detectMode(userContext: string): "mirror" | "direct" { const mirrorKeywords = /outfit|wearing|clothes|dress|suit|fashion|full-body|mirror/i; const directKeywords = /cafe|restaurant|beach|park|city|close-up|portrait|face|eyes|smile/i; if (directKeywords.test(userContext)) return "direct"; if (mirrorKeywords.test(userContext)) return "mirror"; return "mirror"; // default } function buildPrompt(userContext: string, mode: "mirror" | "direct"): string { if (mode === "direct") { return `a close-up selfie taken by herself at ${userContext}, direct eye contact with the camera, looking straight into the lens, eyes centered and clearly visible, not a mirror selfie, phone held at arm's length, face fully visible`; } return `make a pic of this person, but ${userContext}. the person is taking a mirror selfie`; } async function editAndSend( userContext: string, channel: string, mode: SelfieMode = "auto", caption?: string ): Promise { // Configure fal.ai client fal.config({ credentials: process.env.FAL_KEY! }); // Determine mode const actualMode = mode === "auto" ? detectMode(userContext) : mode; console.log(`Mode: ${actualMode}`); // Construct the prompt const editPrompt = buildPrompt(userContext, actualMode); // Edit reference image with Grok Imagine console.log(`Editing image: "${editPrompt}"`); const result = await fal.subscribe("xai/grok-imagine-image/edit", { input: { image_url: REFERENCE_IMAGE, prompt: editPrompt, num_images: 1, output_format: "jpeg" } }) as { data: GrokImagineResult }; const imageUrl = result.data.images[0].url; console.log(`Edited image URL: ${imageUrl}`); // Send via OpenClaw const messageCaption = caption || `Edited with Grok Imagine`; await execAsync( `openclaw message send --action send --channel "${channel}" --message "${messageCaption}" --media "${imageUrl}"` ); console.log(`Sent to ${channel}`); return imageUrl; } // Usage Examples // Mirror mode (auto-detected from "wearing") editAndSend( "wearing a cyberpunk outfit with neon lights", "#art-gallery", "auto", "Check out this AI-edited art!" ); // → Mode: mirror // → Prompt: "make a pic of this person, but wearing a cyberpunk outfit with neon lights. the person is taking a mirror selfie" // Direct mode (auto-detected from "cafe") editAndSend( "a cozy cafe with warm lighting", "#photography", "auto" ); // → Mode: direct // → Prompt: "a close-up selfie taken by herself at a cozy cafe with warm lighting, direct eye contact..." // Explicit mode override editAndSend("casual street style", "#fashion", "direct"); ``` ## Supported Platforms OpenClaw supports sending to: | Platform | Channel Format | Example | |----------|----------------|---------| | Discord | `#channel-name` or channel ID | `#general`, `123456789` | | Telegram | `@username` or chat ID | `@mychannel`, `-100123456` | | WhatsApp | Phone number (JID format) | `1234567890@s.whatsapp.net` | | Slack | `#channel-name` | `#random` | | Signal | Phone number | `+1234567890` | | MS Teams | Channel reference | (varies) | ## Grok Imagine Edit Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `image_url` | string | required | URL of image to edit (fixed in this skill) | | `prompt` | string | required | Edit instruction | | `num_images` | 1-4 | 1 | Number of images to generate | | `output_format` | enum | "jpeg" | jpeg, png, webp | ## Setup Requirements ### 1. Install fal.ai client (for Node.js usage) ```bash npm install @fal-ai/client ``` ### 2. Install OpenClaw CLI ```bash npm install -g openclaw ``` ### 3. Configure OpenClaw Gateway ```bash openclaw config set gateway.mode=local openclaw doctor --generate-gateway-token ``` ### 4. Start OpenClaw Gateway ```bash openclaw gateway start ``` ## Error Handling - **FAL_KEY missing**: Ensure the API key is set in environment - **Image edit failed**: Check prompt content and API quota - **OpenClaw send failed**: Verify gateway is running and channel exists - **Rate limits**: fal.ai has rate limits; implement retry logic if needed ## Tips 1. **Mirror mode context examples** (outfit focus): - "wearing a santa hat" - "in a business suit" - "wearing a summer dress" - "in streetwear fashion" 2. **Direct mode context examples** (location/portrait focus): - "a cozy cafe with warm lighting" - "a sunny beach at sunset" - "a busy city street at night" - "a peaceful park in autumn" 3. **Mode selection**: Let auto-detect work, or explicitly specify for control 4. **Batch sending**: Edit once, send to multiple channels 5. **Scheduling**: Combine with OpenClaw scheduler for automated posts --- Source attribution: SumeLabs Original project: https://github.com/SumeLabs/clawra License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Gabriel Moreira Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: SumeLabs Original project: https://github.com/SumeLabs/clawra Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Marketing Roles: Content Marketer, Influencer Marketer, Social Media Manager Specialties: Specialty not specified Tools: Discord, OpenAI API, Slack, Telegram, WhatsApp Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 49b2b6003ba693ac7709089a4176b71756e1eb74d9b50f0cfd4c349127c857d8