ticruz38 Engagement Replies
Generate AI-powered reply suggestions for social media comments and messages with intelligent tone matching and sentiment awareness.
Capabilities
- Reply Generation: Create contextual reply suggestions for any comment or message
- Tone Matching: Automatically match the tone of the incoming message or choose from 8 different tones
- Quick Templates: Access pre-built response templates for common scenarios
- Sentiment Awareness: Detect sentiment and adjust replies accordingly
- Multiple Suggestions: Get 3 different reply options to choose from
- History Tracking: Save and review all generated replies
Installation
cd skills/engagement-replies
npm install
npm run build
Usage
CLI
# Generate reply suggestions for a comment
npx engagement-replies generate --message "Great post! Really helpful content." --context "blog-post" --author "JohnDoe"
# Generate with specific tone
npx engagement-replies generate -m "Thanks for sharing!" -c "linkedin-comment" -t professional
# Use a quick template
npx engagement-replies template --name "thank-you" --variables '{"name":"John"}'
# List available templates
npx engagement-replies templates
# View sentiment analysis
npx engagement-replies sentiment --message "This is amazing! Love your work!"
# View reply history
npx engagement-replies history --limit 10
Library
import { EngagementRepliesSkill } from '@openclaw/engagement-replies';
const replies = new EngagementRepliesSkill();
// Generate reply suggestions
const suggestions = await replies.generateReplies({
message: "Great post! Really helpful content.",
context: "Blog post about AI tools",
authorName: "JohnDoe",
platform: "twitter",
tone: "friendly",
count: 3
});
console.log(suggestions);
// Returns array of reply options with different approaches
// Analyze sentiment
const sentiment = await replies.analyzeSentiment("This is amazing! Love your work!");
console.log(sentiment);
// { sentiment: 'positive', score: 0.9, emotions: ['joy', 'excitement'] }
// Use a quick template
const template = await replies.getTemplate("thank-you");
const reply = replies.applyTemplate(template, { name: "John", product: "Our Service" });
// Get all templates
const templates = await replies.getTemplates();
// View history
const history = await replies.getHistory(10);
await replies.close();
Reply Types
Platforms
- twitter: Short, concise replies optimized for Twitter/X
- linkedin: Professional tone for business networking
- instagram: Visual-friendly, emoji-supported replies
- facebook: Casual, conversational style
- email: Formal, structured responses
- generic: Platform-agnostic replies
Tones
- professional: Clear, business-appropriate language
- casual: Relaxed, conversational style
- friendly: Warm and approachable
- formal: Proper grammar, sophisticated vocabulary
- enthusiastic: Excited and energetic
- empathetic: Understanding and compassionate
- authoritative: Expert and confident
- witty: Clever and humorous
Sentiment Responses
- Positive: Gratitude, agreement, encouragement
- Negative: Empathy, problem-solving, de-escalation
- Neutral: Informational, helpful, clarifying
- Mixed: Balanced, addressing concerns positively
Templates
Built-in quick response templates:
- thank-you: Express gratitude for positive feedback
- question-response: Answer common questions
- complaint-acknowledgment: Acknowledge issues professionally
- follow-up-request: Encourage further engagement
- appreciation: Show appreciation for support
- welcome: Greet new followers/connections
- apology: Professional apology responses
- clarification: Clear up misunderstandings
Database
Replies are stored in SQLite at ~/.openclaw/skills/engagement-replies/replies.db:
- generated_replies: All generated reply suggestions with metadata
- templates: Quick response templates
- sentiment_cache: Cached sentiment analysis results
No External Dependencies
This skill uses local AI generation patterns and does not require external API keys. It works entirely offline.