Clawra Selfie

Edit Clawra's reference image with Grok Imagine (xAI Aurora) and send selfies to messaging channels via OpenClaw

Security Scan

The skill's instructions match its stated purpose (editing a fixed image and sending it to chat channels), but the runtime instructions require API secrets and local gateway tokens that are not declared in the registry metadata and could permit message-sending or billable API use if provided — this mismatch and potential for misuse merit caution.

Purpose & Capability

The SKILL.md describes editing a fixed reference image via Fal.ai (Grok Imagine) and sending the result through OpenClaw — these requirements are coherent with the skill's description. However, the registry metadata lists no required environment variables or primary credential while the SKILL.md explicitly requires FAL_KEY and OPENCLAW_GATEWAY_TOKEN. That metadata mismatch is unexpected and reduces transparency.

Instruction Scope

The instructions are narrowly scoped: they (1) take a user prompt, (2) call fal.run/xai/grok-imagine-image/edit with a fixed public reference image, and (3) send the returned image URL to channels via the OpenClaw CLI or local gateway. The skill does not instruct reading unrelated files or system secrets. Note: the prompts focus on realistic selfies (face fully visible), which may have privacy/biometric policy implications depending on your environment.

Install Mechanism

This is an instruction-only skill with no install spec and no bundled code. No downloads or package installs are specified, so nothing is written to disk by the skill itself.

Credentials

The SKILL.md requires two environment values: FAL_KEY (Fal.ai API key) and OPENCLAW_GATEWAY_TOKEN (OpenClaw gateway token). Both are plausible for the described workflow, but the registry metadata did not declare these requirements. The gateway token in particular can authorize sending messages to arbitrary channels via the local OpenClaw API; if leaked or too-permissive, it could be abused. Also supplying FAL_KEY enables billable API calls. The absence of declared env vars in metadata is an incoherence that should be resolved before trusting the skill.

Persistence & Privilege

The skill is not always: true and does not request persistent/privileged presence. It does instruct interacting with a local OpenClaw gateway but does not indicate modifying other skills or system-wide settings.

What to consider before installing

Before installing: (1) note the SKILL.md requires FAL_KEY and OPENCLAW_GATEWAY_TOKEN but the registry metadata does not list them — ask the publisher to update metadata to declare required secrets. (2) Understand what those secrets allow: FAL_KEY allows billed calls to fal.ai image-editing APIs; OPENCLAW_GATEWAY_TOKEN authorizes the OpenClaw gateway to send messages to channels (so treat it like a messaging credential). Only provide a minimal-scoped token and avoid sharing it. (3) Confirm the OpenClaw gateway the skill will hit is local/trusted (the docs reference http://localhost:18789); if your gateway is reachable remotely, the risk increases. (4) Consider policy/privacy issues: the skill generates realistic selfies (faces), which may have platform or legal restrictions. (5) Because this is an instruction-only skill with no provenance (source/homepage unknown), prefer running it in an isolated/testing environment first and request the publisher to: declare required env vars in registry metadata, provide a trusted source/homepage, and document token scopes. If you cannot verify those items, proceed cautiously or avoid installing.

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

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:

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 <USER_CONTEXT>. the person is taking a mirror selfie"

# Mode 2: Direct Selfie
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"

# 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:

{
  "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:

openclaw message send \
  --action send \
  --channel "<TARGET_CHANNEL>" \
  --message "<CAPTION_TEXT>" \
  --media "<IMAGE_URL>"

Alternative: Direct API call

curl -X POST "http://localhost:18789/message" \
  -H "Authorization: Bearer $OPENCLAW_GATEWAY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "action": "send",
    "channel": "<TARGET_CHANNEL>",
    "message": "<CAPTION_TEXT>",
    "media": "<IMAGE_URL>"
  }'

Complete Script Example

#!/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 <user_context> <channel> [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

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<string> {
  // 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)	[e-mail]
Slack	#channel-name	#random
Signal	Phone number	[phone]
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)

npm install @fal-ai/client

2. Install OpenClaw CLI

npm install -g openclaw

3. Configure OpenClaw Gateway

openclaw config set gateway.mode=local
openclaw doctor --generate-gateway-token

4. Start OpenClaw Gateway

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