person-analyzer

What this skill does

# Person Intelligence Analyzer

Comprehensive multi-platform intelligence analysis combining LinkedIn, Twitter/X, Reddit, GitHub, and web presence data to create actionable intelligence reports with cross-platform personality insights.

## Analysis Workflow

Execute phases sequentially, adapting depth based on available data and user requirements.

### Phase 1: Initial Data Collection

**Starting with LinkedIn Profile URL:**
1. Use `get_linkedin_profile` with full parameters (education, experience, skills)
2. Extract and save the **full URN** (format: `urn:li:fsd_profile:ACoAAABCDEF`) - this is critical for all subsequent API calls
3. Also extract: company URN, current role, location, connections count
4. Record profile completeness for confidence scoring

**IMPORTANT - URN Format:** 
Always use the complete URN format `urn:li:fsd_profile:ACoAAABCDEF` from the profile response for all subsequent calls to `get_linkedin_user_posts`, `get_linkedin_user_comments`, and `get_linkedin_user_reactions`. Do not use shortened versions or profile URLs.

**Starting with Name + Context:**
1. Use `search_linkedin_users` with all available filters:
   - Name, title, company keywords, location, school
2. If multiple matches: present top 3-5 candidates with distinguishing details
3. After user confirmation, proceed with confirmed profile

**Critical Data Points to Capture:**
- Current company and role (with start date)
- Previous roles (last 2-3 positions)
- Education background
- Skills and endorsements
- Connection count (indicator of network size)
- Profile headline and summary

### Phase 2: Activity & Engagement Analysis

**Content Analysis (Posts):**
1. Use `get_linkedin_user_posts` with the full URN (format: `urn:li:fsd_profile:ACoAAABCDEF`)
   - Count: 20-50 depending on activity level
   - Posted after filter: last 90 days for active users, 180 days if low activity
2. Analyze for:
   - Topics and themes (use clustering: technical, leadership, industry trends, personal)
   - Engagement metrics (likes, comments per post - calculate averages)
   - Posting frequency (calculate posts per week/month)
   - Content style (thought leadership, sharing, personal stories, company updates)
   - Language and tone

**Engagement Analysis (Comments & Reactions):**
1. Use `get_linkedin_user_comments` with the full URN (format: `urn:li:fsd_profile:ACoAAABCDEF`)
   - Count: 30
2. Use `get_linkedin_user_reactions` with the full URN (format: `urn:li:fsd_profile:ACoAAABCDEF`)
   - Count: 50
3. Analyze for:
   - Who they engage with (seniority levels, industries)
   - Topics that spark their engagement
   - Engagement style (supportive, challenging, informational)
   - Response patterns (quick reactions vs thoughtful comments)

**CRITICAL:** All three tools (`get_linkedin_user_posts`, `get_linkedin_user_comments`, `get_linkedin_user_reactions`) require the complete URN in the format `urn:li:fsd_profile:ACoAAABCDEF` obtained from Phase 1. Using LinkedIn profile URLs or partial URNs will result in errors.

**Output: Engagement Profile**
- Primary content themes (ranked by frequency)
- Engagement level: High/Medium/Low (posts per month, reactions per week)
- Influence indicators: follower count, average post engagement rate
- Communication style: formal/casual, technical/general, etc.

### Phase 3: Company Intelligence

**Current Company Deep Dive:**
1. Use `get_linkedin_company` with company URN from profile
2. Extract:
   - Company size, industry, specialties
   - Growth indicators (employee count trends if available)
   - Company description and mission
   - Recent updates/news

3. Use `get_linkedin_company_posts` (count: 20)
   - Analyze company communication themes
   - Identify strategic priorities
   - Note any mentions of funding, hiring, expansion

4. Use `duckduckgo_search` for recent news:
   - "[Company name] funding news"
   - "[Company name] expansion launch product"
   - Prioritize results from last 6 months

**Company Social Media Presence:**

5. **Company Twitter/X Analysis:**
   - Use `search_twitter_users` to find official company account: "[Company Name] official"
   - If found, use `get_twitter_user` for profile stats
   - Use `get_twitter_user_posts` (count: 20-30) to analyze:
     - Product announcements and launches
     - Company culture and values
     - Engagement with customers and community
     - Hiring announcements (growth signals)
     - Technical content (if tech company)
   - Use `search_twitter_posts` for company mentions: "[Company Name]"
     - Customer sentiment (complaints vs praise)
     - Industry discussion about the company
     - Competitor comparisons
     - Notable tweets from employees

6. **Company Reddit Presence:**
   - Use `search_reddit_posts` for company mentions: "[Company Name]"
   - Look for:
     - r/startups discussions about the company
     - Industry-specific subreddit mentions (r/SaaS, r/artificial, etc.)
     - Customer experiences and reviews
     - Technical discussions about their product/platform
     - Hiring experiences (Glassdoor-like insights)
     - Founder/team AMAs or discussions
   - Sentiment analysis: positive/negative/neutral community perception
   - Pain points mentioned by users/customers

**Company Context Analysis:**
- Business model and revenue streams
- Technology stack (if tech company)
- Market position and competitors
- Recent achievements or challenges
- Cultural indicators from company posts
- **Social sentiment** (Twitter mentions, Reddit discussions)
- **Community engagement** (how company responds on social platforms)
- **Growth signals** (hiring tweets, expansion announcements on Twitter)
- **Customer pain points** (Reddit complaints, Twitter issues)

### Phase 4: Multi-Platform Intelligence Enrichment

**A. Twitter/X Analysis (if handle found or identifiable):**

1. **Find Twitter Handle:**
   - Check LinkedIn profile bio/description for @username
   - Use `search_twitter_users` with name if not found: "[First Name] [Last Name] [Company]"
   - Verify match by checking bio, profile description

2. **Profile Analysis:**
   - Use `get_twitter_user` with username
   - Extract: follower count, following count, tweet count, bio, location
   - Note: verification status, profile creation date

3. **Content Analysis:**
   - Use `get_twitter_user_posts` (count: 50-100 recent tweets)
   - Analyze for:
     - Technical expertise signals (code snippets, tech discussions)
     - Industry opinions and hot takes
     - Personal interests and hobbies
     - Engagement with other thought leaders
     - Retweets vs original content ratio
   - Calculate: tweets per day, avg engagement rate

4. **Topic Discovery:**
   - Use `search_twitter_posts` with person's key interests: "[topic] from:@username"
   - Identify recurring themes and expertise areas
   - Note controversial or strongly-held opinions

**B. Reddit Activity (if username discoverable):**

1. **Find Reddit Presence:**
   - Search for username from other platforms
   - Use `search_reddit_posts` with name/company mentions
   - Look for: "AMA" posts, technical discussions, community contributions

2. **Content Analysis:**
   - Use `search_reddit_posts` with username if known: "author:[username]"
   - Analyze for:
     - Subreddit preferences (which communities they're active in)
     - Technical depth of contributions
     - Helping behavior vs self-promotion ratio
     - Community reputation indicators

3. **Topic Expertise:**
   - Use `search_reddit_posts` for specific topics: "[topic] [username or company]"
   - Identify where they're seen as expert/helpful
   - Note any popular posts or discussions they started

**C. Instagram Presence (optional, if B2C relevant or personal brand focus):**

1. **Profile Discovery:**
   - Check if mentioned in LinkedIn or Twitter
   - Use `search_instagram_posts` with hashtags: "#[name] #[company]"
   - Use `get_instagram_user` if handle known

2. **Content Style:**
   - Use `get_instagram_user_posts` (count: 20-30)