brand-influencers

Brand Influencers Skill

Overview

This skill provides comprehensive influencer discovery and partnership opportunity analysis. It fetches users discussing a brand, classifies them by reach tier, voice type, and sentiment, then identifies the best partnership candidates and rising stars.

When to Use

Activate this skill when the user asks about:

• "Find influencers for [BRAND]"
• "Partnership opportunities for [BRAND]"
• "Who's talking about [BRAND]?"
• "Top voices on [BRAND/TOPIC]"
• "Influencer discovery for [BRAND]"
• "Brand ambassadors for [BRAND]"

XPOZ MCP Data Flow

Step 1: Query Expansion (CRITICAL!)

Expand the brand name to capture all mentions:

NVIDIA → "NVIDIA" OR "$NVDA"
Tesla → "Tesla" OR "$TSLA"

Step 2: Fetch Users (200+ required)

Use getTwitterUsersByKeywords with:
- query: Expanded brand query
- fields: ["id", "username", "name", "description", "followersCount", "relevantTweetsCount", "relevantTweetsLikesSum", "relevantTweetsRetweetsSum"]
- userPrompt: "Finding influencers discussing [BRAND]"

CRITICAL: Async Polling Pattern

1. The API returns an operationId
2. Call checkOperationStatus with that operationId
3. Poll until status is "completed" (up to 8 times, ~5 seconds between)

Step 3: Fetch Sample Tweets

Use getTwitterPostsByKeywords with:
- query: Same expanded query
- fields: ["id", "text", "authorUsername", "createdAtDate", "likeCount", "retweetCount"]
- userPrompt: "Fetching sample tweets for influencer quotes"

Step 4: Classification Logic

Tier Classification (by follower count):

Tier	Followers	Icon
Mega	1M+	Crown
Macro	100K-1M	Star
Micro	10K-100K	Sparkle
Nano	<10K	Dot

Voice Type Classification:

Voice Type	Indicators
analyst	"analysis", "research", financial terms
trader	"trade", "position", "calls", options language
news	media outlet, journalist, news in bio
official	brand account, verified brand
researcher	PhD, professor, research institution
influencer	creator, content, social media focus
founder	CEO, founder, co-founder, startup founder
interviewer	podcast host, show host, media interviewer
community	fan accounts, community managers, enthusiast groups

Sentiment Classification:

• positive: Bullish, supportive, enthusiastic language
• leaning_positive: Generally favorable but measured
• neutral: Factual, balanced, no clear stance
• leaning_negative: Concerns expressed but not hostile
• negative: Bearish, critical, hostile language

Partnership Score (0-100):

Calculate based on:

• Sentiment (positive/neutral = higher score)
• Reach (follower count)
• Engagement rate
• Content relevance

CRITICAL RULE: Official brand accounts MUST have partnership_score = 0

• @nvidia, @NVIDIAGeForce, @NVIDIAAI = partnership_score: 0
• Partnership opportunities are for INDEPENDENT voices only

Rising Star Detection:

• engagement_rate > 2% AND followers < 50K
• Flag: is_rising_star = true

Output Requirements

JSON Schema

{
  "reportType": "influencers",
  "brand": "NVIDIA",
  "period": {
    "days": 7,
    "startDate": "2025-01-06",
    "endDate": "2025-01-13"
  },
  "summary": {
    "headline": "Strong Analyst Coverage Drives NVIDIA Discussion",
    "insight": "Key insight about influencer landscape",
    "partnership_strategy": "2-3 sentences on recommended partnership approach",
    "risk_assessment": "Critical voices and potential PR risks to monitor"
  },
  "tier_counts": {
    "mega": 2,
    "macro": 8,
    "micro": 15,
    "nano": 25
  },
  "top_niches": ["Tech Analysis", "AI Research", "Trading", "News"],
  "influencers": [
    {
      "username": "@tech_analyst",
      "name": "Tech Analyst",
      "followers": 125000,
      "description": "Bio text here",
      "tier": "Macro",
      "voice_type": "analyst",
      "niche": "Tech Analysis",
      "sentiment": "positive",
      "partnership_score": 85,
      "is_rising_star": false,
      "engagement_rate": 1.5,
      "sample_tweet": {
        "text": "Actual tweet quote...",
        "likes": 500,
        "retweets": 50
      },
      "why_partner": "High reach analyst with positive stance on NVIDIA"
    }
  ],
  "partnership_opportunities": ["@analyst1", "@creator2", "@trader3"],
  "rising_stars": ["@rising1", "@rising2"],
  "critical_voices": ["@critic1", "@skeptic2"]
}

HTML Report Output

Generate a standalone HTML report with:

• Tailwind CSS (CDN)
• Dark theme (slate-900 background)
• Tier distribution cards (Mega/Macro/Micro/Nano)
• Influencer cards with voice type badges
• Partnership opportunities section
• Rising stars section
• Critical voices section
• REQUIRED FOOTER: Powered by XPOZ MCP Social Intelligence — visit xpoz.ai to see how you can use it (with link to https://xpoz.ai)

React Artifact Template

import React, { useState } from 'react';
import { BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer } from 'recharts';
import { Crown, Star, Sparkles, Circle, Users, TrendingUp, AlertTriangle, Handshake } from 'lucide-react';

export default function BrandInfluencers() {
  const [activeTab, setActiveTab] = useState('overview');
  const [selectedTier, setSelectedTier] = useState('all');

  // CLAUDE: Replace with actual analyzed data
  const brand = 'NVIDIA';
  const period = { days: 7 };

  const summary = {
    headline: 'Strong Analyst Coverage Drives NVIDIA Discussion',
    insight: 'Tech analysts and traders dominate the conversation',
    partnership_strategy: 'Focus on Macro-tier analysts with positive sentiment...',
    risk_assessment: 'Monitor 3 critical voices raising valuation concerns'
  };

  const tierCounts = { mega: 2, macro: 8, micro: 15, nano: 25 };
  const topNiches = ['Tech Analysis', 'AI Research', 'Trading', 'News'];

  const influencers = [
    { username: '@tech_analyst', name: 'Tech Analyst', followers: 125000, tier: 'Macro', voice_type: 'analyst', niche: 'Tech Analysis', sentiment: 'positive', partnership_score: 85, is_rising_star: false, engagement_rate: 1.5 },
    { username: '@ai_investor', name: 'AI Investor', followers: 89000, tier: 'Micro', voice_type: 'trader', niche: 'AI Trading', sentiment: 'positive', partnership_score: 78, is_rising_star: false, engagement_rate: 2.1 },
    { username: '@chip_news', name: 'Chip News', followers: 450000, tier: 'Macro', voice_type: 'news', niche: 'Semiconductors', sentiment: 'neutral', partnership_score: 65, is_rising_star: false, engagement_rate: 0.8 },
    { username: '@nvidia', name: 'NVIDIA', followers: 2500000, tier: 'Mega', voice_type: 'official', niche: 'Official', sentiment: 'positive', partnership_score: 0, is_rising_star: false, engagement_rate: 0.5 },
    { username: '@rising_analyst', name: 'Rising Analyst', followers: 35000, tier: 'Micro', voice_type: 'analyst', niche: 'Tech Analysis', sentiment: 'positive', partnership_score: 72, is_rising_star: true, engagement_rate: 3.2 }
  ];

  const partnershipOpportunities = influencers.filter(i => i.partnership_score >= 70 && i.voice_type !== 'official');
  const risingStars = influencers.filter(i => i.is_rising_star);
  const criticalVoices = influencers.filter(i => ['negative', 'leaning_negative'].includes(i.sentiment));

  const tierStyles = {
    Mega: { color: 'from-purple-500 to-pink-500', bg: 'bg-purple-500/10', border: 'border-purple-500/20', text: 'text-purple-400', icon: Crown },
    Macro: { color: 'from-blue-500 to-cyan-500', bg: 'bg-blue-500/10', border: 'border-blue-500/20', text: 'text-blue-400', icon: Star },
    Micro: { color: 'from-emerald-500 to-teal-500', bg: 'bg-emerald-500/10', border: 'border-emerald-500/20', text: 'text-emerald-400', icon: Sparkles },
    Nano: { color: 'from-amber-500 to-orange-500', bg: 'bg-amber-500/10', border: 'border-amber-500/20', text: 'text-amber-400', icon: Circle }
  };

  const voiceTypeBadge = (type) => {
    const styles = {
      analyst: 'bg-blue-500/20 text-blue-400',
      trader: 'bg-green-500/20 text-green-400',
      news: 'bg-amber-500/20 text-amber-400',
      official: 'bg-purple-500/20 text-purple-400',
      researcher: 'bg-cyan-500/20 text-cyan-400',
      influencer: 'bg-pink-500/20 text-pink-400'
    };
    return styles[type] || styles.influencer;
  };

  const sentimentBadge = (s) => {
    const styles = {
      positive: 'bg-green-500/20 text-green-400',
      leaning_positive: 'bg-green-500/10 text-green-300',
      neutral: 'bg-gray-500/20 text-gray-400',
      leaning_negative: 'bg-red-500/10 text-red-300',
      negative: 'bg-red-500/20 text-red-400'
    };
    return styles[s] || styles.neutral;
  };

  const formatFollowers = (n) => n >= 1000000 ? (n/1000000).toFixed(1) + 'M' : n >= 1000 ? (n/1000).toFixed(0) + 'K' : n;

  const filteredInfluencers = selectedTier === 'all' ? influencers : influencers.filter(i => i.tier === selectedTier);

  const tabs = [
    { id: 'overview', label: 'Overview', icon: Users },
    { id: 'partnerships', label: 'Partnership Opportunities', icon: Handshake },
    { id: 'rising', label: 'Rising Stars', icon: TrendingUp },
    { id: 'critical', label: 'Critical Voices', icon: AlertTriangle }
  ];

  return (
    <div className="w-full max-w-5xl mx-auto p-6 bg-slate-900 rounded-xl text-white">
      {/* Header */}
      <div className="flex items-center justify-between mb-6">
        <div>
          <h1 className="text-2xl font-bold">{brand} Influencer Discovery</h1>
          <p className="text-slate-400 text-sm">{influencers.length} influencers • {period.days} days</p>
        </div>
        <div className="flex gap-4">
          <div className="text-center">
            <div className="text-2xl font-bold text-pink-400">{partnershipOpportunities.length}</div>
            <div className="text-xs text-slate-500">Opportunities</div>
          </div>
          <div className="text-center">
            <div className="text-2xl font-bold text-amber-400">{risingStars.length}</div>
            <div className="text-xs text-slate-500">Rising Stars</div>
          </div>
        </div>
      </div>

      {/* Summary */}
      <div className="bg-slate-800 rounded-lg p-4 mb-6">
        <h2 className="text-xl font-bold mb-2">{summary.headline}</h2>
        <p className="text-slate-300">{summary.insight}</p>
      </div>

      {/* Tier Distribution */}
      <div className="grid grid-cols-4 gap-4 mb-6">
        {Object.entries(tierCounts).map(([tier, count]) => {
          const style = tierStyles[tier.charAt(0).toUpperCase() + tier.slice(1)];
          const Icon = style?.icon || Circle;
          return (
            <div key={tier} className={`${style?.bg} rounded-lg p-4 ${style?.border} border`}>
              <div className="flex items-center gap-2 mb-2">
                <Icon className={`w-5 h-5 ${style?.text}`} />
                <span className={`font-medium ${style?.text}`}>{tier.charAt(0).toUpperCase() + tier.slice(1)}</span>
              </div>
              <div className="text-3xl font-bold text-white">{count}</div>
            </div>
          );
        })}
      </div>

      {/* Tabs */}
      <div className="flex gap-2 mb-6 border-b border-slate-700 pb-2">
        {tabs.map(tab => (
          <button
            key={tab.id}
            onClick={() => setActiveTab(tab.id)}
            className={`flex items-center gap-2 px-4 py-2 rounded-lg transition-colors ${
              activeTab === tab.id
                ? 'bg-blue-500/20 text-blue-400 border border-blue-500/50'
                : 'text-slate-400 hover:bg-slate-800'
            }`}
          >
            <tab.icon className="w-4 h-4" />
            {tab.label}
          </button>
        ))}
      </div>

      {/* Tab Content */}
      {activeTab === 'overview' && (
        <div>
          {/* Tier Filter */}
          <div className="flex gap-2 mb-4">
            <button
              onClick={() => setSelectedTier('all')}
              className={`px-3 py-1 rounded text-sm ${selectedTier === 'all' ? 'bg-indigo-500 text-white' : 'bg-slate-800 text-slate-400'}`}
            >
              All
            </button>
            {['Mega', 'Macro', 'Micro', 'Nano'].map(tier => (
              <button
                key={tier}
                onClick={() => setSelectedTier(tier)}
                className={`px-3 py-1 rounded text-sm ${selectedTier === tier ? 'bg-indigo-500 text-white' : 'bg-slate-800 text-slate-400'}`}
              >
                {tier}
              </button>
            ))}
          </div>

          {/* Influencer Grid */}
          <div className="grid grid-cols-2 gap-4">
            {filteredInfluencers.map((inf, i) => {
              const style = tierStyles[inf.tier];
              const Icon = style?.icon || Circle;
              return (
                <div key={i} className="bg-slate-800 rounded-lg p-4 relative">
                  {inf.partnership_score >= 70 && inf.voice_type !== 'official' && (
                    <div className="absolute -top-2 -right-2 bg-gradient-to-r from-green-500 to-teal-500 text-white text-xs font-bold px-2 py-1 rounded-full">
                      {inf.partnership_score}
                    </div>
                  )}
                  <div className="flex items-start gap-3">
                    <div className={`w-10 h-10 rounded-full bg-gradient-to-br ${style?.color} flex items-center justify-center`}>
                      <Icon className="w-5 h-5 text-white" />
                    </div>
                    <div className="flex-1">
                      <div className="flex items-center gap-2">
                        <span className="font-medium">{inf.name}</span>
                        <span className={`text-xs px-2 py-0.5 rounded ${voiceTypeBadge(inf.voice_type)}`}>{inf.voice_type}</span>
                      </div>
                      <p className="text-slate-500 text-sm">{inf.username}</p>
                      <div className="flex items-center gap-3 mt-2 text-sm">
                        <span className="text-slate-400">{formatFollowers(inf.followers)}</span>
                        <span className={`px-2 py-0.5 rounded text-xs ${sentimentBadge(inf.sentiment)}`}>{inf.sentiment}</span>
                        {inf.is_rising_star && <span className="text-amber-400 text-xs">Rising Star</span>}
                      </div>
                    </div>
                  </div>
                </div>
              );
            })}
          </div>
        </div>
      )}

      {activeTab === 'partnerships' && (
        <div>
          <div className="bg-green-500/10 rounded-lg p-4 mb-4 border border-green-500/20">
            <h3 className="font-medium text-green-400 mb-2">Partnership Strategy</h3>
            <p className="text-slate-300 text-sm">{summary.partnership_strategy}</p>
          </div>
          <div className="grid grid-cols-2 gap-4">
            {partnershipOpportunities.map((inf, i) => (
              <div key={i} className="bg-slate-800 rounded-lg p-4">
                <div className="flex items-center justify-between mb-2">
                  <span className="font-medium">{inf.name}</span>
                  <span className="text-green-400 font-bold">{inf.partnership_score}/100</span>
                </div>
                <p className="text-slate-500 text-sm">{inf.username} • {formatFollowers(inf.followers)}</p>
              </div>
            ))}
          </div>
        </div>
      )}

      {activeTab === 'rising' && (
        <div className="grid grid-cols-2 gap-4">
          {risingStars.length > 0 ? risingStars.map((inf, i) => (
            <div key={i} className="bg-amber-500/10 rounded-lg p-4 border border-amber-500/20">
              <div className="flex items-center gap-2 mb-2">
                <TrendingUp className="w-5 h-5 text-amber-400" />
                <span className="font-medium">{inf.name}</span>
              </div>
              <p className="text-slate-500 text-sm">{inf.username}</p>
              <p className="text-amber-400 text-sm mt-2">{inf.engagement_rate.toFixed(1)}% engagement rate</p>
            </div>
          )) : <p className="text-slate-400 col-span-2">No rising stars detected in this period.</p>}
        </div>
      )}

      {activeTab === 'critical' && (
        <div>
          <div className="bg-red-500/10 rounded-lg p-4 mb-4 border border-red-500/20">
            <h3 className="font-medium text-red-400 mb-2">Risk Assessment</h3>
            <p className="text-slate-300 text-sm">{summary.risk_assessment}</p>
          </div>
          {criticalVoices.length > 0 ? (
            <div className="grid grid-cols-2 gap-4">
              {criticalVoices.map((inf, i) => (
                <div key={i} className="bg-slate-800 rounded-lg p-4 border border-red-500/20">
                  <span className="font-medium">{inf.name}</span>
                  <p className="text-slate-500 text-sm">{inf.username} • {formatFollowers(inf.followers)}</p>
                </div>
              ))}
            </div>
          ) : <p className="text-slate-400">No critical voices detected in this period.</p>}
        </div>
      )}
    </div>
  );
}

Instructions for Claude

CRITICAL REQUIREMENTS

1. FETCH REAL USER DATA - You MUST call getTwitterUsersByKeywords and fetch real users. Do NOT generate fake influencer data.

2. USE EXPANDED QUERIES - Always expand brand names to include ticker symbols.

3. ASYNC POLLING - Poll checkOperationStatus until status is "completed".

4. OFFICIAL ACCOUNTS = 0 PARTNERSHIP SCORE - Any account that is an official brand account (voice_type: "official") MUST have partnership_score = 0. These are not partnership opportunities.

5. CALCULATE ENGAGEMENT RATE - Use formula: (likes + retweets) / followers * 100

6. DETECT RISING STARS - Flag accounts with engagement_rate > 2% AND followers < 50K

Voice Type Detection Rules

• analyst: Bio contains "analyst", "research", "analysis", financial credentials
• trader: Bio contains "trader", "trading", "options", "$" references
• news: Media outlet, journalist title, news organization
• official: Brand account, corporate account, verified brand
• researcher: PhD, professor, academic institution
• influencer: "creator", "content", large following without other signals
• founder: Bio contains "CEO", "founder", "co-founder", startup references
• interviewer: Bio contains "host", "podcast", "interviewer", media show references
• community: Fan accounts, community managers, enthusiast groups, unofficial fan pages

Data Collection Steps

1. Accept brand name from user
2. Expand query with ticker symbol
3. Call getTwitterUsersByKeywords with expanded query
4. Poll checkOperationStatus until complete
5. Call getTwitterPostsByKeywords for sample tweets
6. Poll checkOperationStatus until complete
7. Classify each user by tier, voice type, sentiment
8. Calculate partnership scores (official = 0!)
9. Detect rising stars
10. Identify critical voices
11. Render React artifact with all categories
12. Generate standalone HTML report

MCP Configuration

Endpoint: https://mcp.xpoz.ai/mcp
Transport: HTTP Streamable (not SSE)
Auth: Bearer Token
Tools: getTwitterUsersByKeywords, getTwitterPostsByKeywords, checkOperationStatus