Social Listener

Monitors Reddit, Hacker News, Product Hunt, Twitter/X, and industry forums for brand mentions, category discussions, and competitor mentions. Uses WebSearch with site-specific operators to surface real-time conversations relevant to your agency and ICP. Outputs categorized mentions with sentiment analysis and engagement potential scoring.

Prerequisites

• agency.config.json at repo root with agency, services, icp, and outreach sections
• WebSearch tool available
• Optional: crm-writer skill for logging high-value mentions to CRM

Phase 0: Intake

1. Read agency.config.json from the project root.
2. Extract:
   • agency.name, agency.domain -- brand identity to monitor
   • services[].name, services[].keywords -- service categories to track
   • icp.primary_keywords, icp.secondary_keywords -- topic relevance signals
   • icp.segments[].industries -- industry verticals to monitor
   • icp.negative_keywords -- filter out self-promotion noise
   • case_studies[].name -- client names to track mentions of
3. Accept parameters:
   • platforms -- list of platforms to monitor (default: all)
   • competitors -- competitor names/domains to track (default: none, user must supply)
   • time_window -- lookback period (default: "past 3 days")
   • mention_types -- filter by type: brand | category | competitor | pain_point (default: all)
   • max_results -- max mentions to return (default: 30)

Phase 1: Query Generation

Build three query categories, each with platform-specific syntax.

Brand Mention Queries

Track direct mentions of the agency, founder, and clients:

• "{agency_name}" across all platforms
• "{agency_domain}" for link mentions
• "{founder_name}" "{agency_name}" for attributed mentions
• "{case_study_name}" "{service_keyword}" for client-related discussions

Category Discussion Queries

Track conversations in your service categories:

Reddit:

• site:reddit.com/r/shopify "{service_keyword}" after:{date}
• site:reddit.com/r/ecommerce "{industry}" "{intent_keyword}"
• Target subreddits: r/shopify, r/ecommerce, r/smallbusiness, r/DTC, r/Entrepreneur, r/startups, r/digital_marketing

Hacker News:

• site:news.ycombinator.com "{service_keyword}" OR "{industry_keyword}"
• site:news.ycombinator.com "Show HN" "{industry_keyword}"

Product Hunt:

• site:producthunt.com "{industry}" OR "{service_keyword}"
• Focus on newly launched products in ICP industries

Twitter/X:

• site:twitter.com OR site:x.com "{service_keyword}" "{intent_keyword}"
• site:twitter.com OR site:x.com "{agency_name}" OR "{agency_domain}"

Industry Forums:

• site:community.shopify.com "{service_keyword}"
• site:indiehackers.com "{industry}" "{service_keyword}"
• site:dev.to "{service_keyword}" for technical discussions

Competitor Mention Queries

For each competitor provided:

• "{competitor_name}" review OR feedback OR experience
• "{competitor_name}" vs OR alternative OR switch
• "{competitor_name}" complaint OR issue OR problem
• "{competitor_name}" "{service_keyword}"

Query generation rules:

• Generate 2-3 queries per platform per category.
• Prioritize recency: always include time filters where supported.
• Total queries per scan: 20-35 across all platforms and categories.
• Rotate keywords across queries to maximize coverage.

Phase 2: Search Execution

Execute searches using WebSearch with rate limiting:

• Max 3 concurrent searches at any time.
• 2-second pause between batches of 3.
• Process results as they arrive; do not wait for all to complete.

For each result, extract:

• url -- source URL
• title -- page/post title
• snippet -- text excerpt from search result
• platform -- inferred from URL domain
• posted_date -- if visible in the result
• author -- if identifiable from snippet or title

Phase 3: Mention Classification

Classify each mention into one of four categories:

1. Brand Mention: Direct reference to agency name, domain, founder, or clients
2. Category Discussion: Conversations about services you offer (without naming you)
3. Competitor Mention: References to competitors you're tracking
4. Pain Point Signal: Prospects expressing frustration or need in your service area

Sentiment Analysis

Score each mention's sentiment:

• POSITIVE: Praise, recommendation, success story, excitement
• NEUTRAL: Informational, question, comparison without strong opinion
• NEGATIVE: Complaint, frustration, criticism, churn signal
• MIXED: Contains both positive and negative elements

Engagement Potential Scoring

Rate each mention's engagement opportunity (1-10):

• 9-10: Direct question seeking help in your service area, high-traffic thread, no existing expert response
• 7-8: Active discussion in your niche, multiple participants, room for expert contribution
• 5-6: Relevant topic but already well-answered, or lower traffic
• 3-4: Tangentially related, limited engagement opportunity
• 1-2: Informational only, no engagement path

Phase 4: Entity Extraction

For each classified mention, produce structured output:

{
  "mention_id": "auto-generated sequential ID",
  "category": "brand | category | competitor | pain_point",
  "platform": "Reddit | HackerNews | ProductHunt | Twitter | ShopifyCommunity | IndieHackers | DevTo",
  "url": "https://...",
  "title": "Post or thread title",
  "snippet": "Relevant excerpt (max 300 chars)",
  "author": "Username or name if identifiable",
  "posted_date": "ISO date or relative",
  "sentiment": "POSITIVE | NEUTRAL | NEGATIVE | MIXED",
  "engagement_score": 7,
  "engagement_reason": "Active thread, OP seeking Shopify CRO help, no expert reply yet",
  "competitor_mentioned": "CompetitorName or null",
  "keywords_matched": ["shopify CRO", "conversion rate"],
  "suggested_action": "ENGAGE | MONITOR | RESPOND | IGNORE",
  "suggested_response": "Brief outline of what to say if action is ENGAGE or RESPOND"
}

Action rules:

• ENGAGE: High engagement score (7+), category or pain_point type, no expert has replied
• RESPOND: Brand mention that is negative or a question directed at you
• MONITOR: Competitor mention or ongoing discussion worth tracking
• IGNORE: Low relevance, already resolved, or stale thread

Phase 5: Dedup & Filter

1. Remove exact URL duplicates.
2. Merge mentions from different platforms about the same underlying event (e.g., a Product Hunt launch discussed on Reddit and HN).
3. Apply negative keyword filter: discard self-promotion matches.
4. Apply recency filter: flag anything outside the time_window as STALE.

Phase 6: Output

Present results grouped by category, sorted by engagement score within each group:

SOCIAL LISTENING REPORT
Period: {time_window}
Platforms scanned: {platform_list}

BRAND MENTIONS ({count}):
1. [{platform}] {sentiment} -- "{title}" -- Engagement: {score}/10
   URL: ...
   Action: {suggested_action}

CATEGORY DISCUSSIONS ({count}):
1. [{platform}] {sentiment} -- "{title}" -- Engagement: {score}/10
   URL: ...
   Action: {suggested_action}

COMPETITOR MENTIONS ({count}):
1. [{platform}] {sentiment} -- "{competitor}" -- "{title}"
   URL: ...

PAIN POINT SIGNALS ({count}):
1. [{platform}] -- "{title}" -- Engagement: {score}/10
   URL: ...
   Suggested response: ...

SUMMARY:
- Total mentions: {N}
- Actionable (ENGAGE/RESPOND): {count}
- Sentiment breakdown: {pos}/{neutral}/{neg}/{mixed}
- Top platform by volume: {platform}
- Top competitor mentioned: {competitor} ({count} mentions)

Return the full structured JSON array alongside the formatted summary.

Phase 7: CRM Logging

If crm-writer is available and user approves:

• Log ENGAGE and RESPOND items to the CRM pipeline tab with columns: Date, Platform, Category, URL, Sentiment, Engagement Score, Action, Status
• Set initial status: "PENDING_RESPONSE"

Example Usage

Trigger phrases:

• "Monitor social mentions"
• "What are people saying about us?"
• "Run social listener"
• "Track competitor mentions on Reddit"
• "Find discussions about Shopify CRO this week"
• "Scan Reddit and HN for category discussions"

User: Run social listener for the past week, track competitors WebSavvy and Starter Labs
Assistant: [reads config, builds brand/category/competitor queries across Reddit/HN/ProductHunt/Twitter/forums, executes with rate limiting, classifies and scores mentions, presents categorized report with engagement recommendations]

User: Monitor Reddit and Shopify Community for pain points about Shopify CRO
Assistant: [same flow limited to 2 platforms, filtered to pain_point category]