| name | person-analyzer |
| description | Deep multi-platform intelligence analysis combining LinkedIn (profile, posts, activity), Twitter/X (tweets, engagement), Reddit (discussions, community), web presence (articles, GitHub, blogs), and company intelligence. Use when analyzing people for networking, sales, partnerships, or recruitment. Accepts LinkedIn URL or name+context. Produces comprehensive cross-platform reports with conversation strategies and strategic value assessment for AnySite. |
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:
- Use
get_linkedin_profile with full parameters (education, experience, skills)
- Extract and save the full URN (format:
urn:li:fsd_profile:ACoAAABCDEF) - this is critical for all subsequent API calls
- Also extract: company URN, current role, location, connections count
- 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:
- Use
search_linkedin_users with all available filters:
- Name, title, company keywords, location, school
- If multiple matches: present top 3-5 candidates with distinguishing details
- 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):
- 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
- 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):
- Use
get_linkedin_user_comments with the full URN (format: urn:li:fsd_profile:ACoAAABCDEF)
- Use
get_linkedin_user_reactions with the full URN (format: urn:li:fsd_profile:ACoAAABCDEF)
- 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:
-
Use get_linkedin_company with company URN from profile
-
Extract:
- Company size, industry, specialties
- Growth indicators (employee count trends if available)
- Company description and mission
- Recent updates/news
-
Use get_linkedin_company_posts (count: 20)
- Analyze company communication themes
- Identify strategic priorities
- Note any mentions of funding, hiring, expansion
-
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:
-
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
-
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):
-
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
-
Profile Analysis:
- Use
get_twitter_user with username
- Extract: follower count, following count, tweet count, bio, location
- Note: verification status, profile creation date
-
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
-
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):
-
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
-
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
-
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):
-
Profile Discovery:
- Check if mentioned in LinkedIn or Twitter
- Use
search_instagram_posts with hashtags: "#[name] #[company]"
- Use
get_instagram_user if handle known
-
Content Style:
- Use
get_instagram_user_posts (count: 20-30)
- Analyze for: personal brand vs professional content
- Note: visual style, posting frequency, engagement rate
D. Web Intelligence & Media Presence:
-
Professional Presence:
duckduckgo_search: "[Name] [Company] speaker conference"duckduckgo_search: "[Name] interview podcast"duckduckgo_search: "[Name] article blog post"
-
Expertise & Thought Leadership:
duckduckgo_search: "[Name] expertise [primary topic from posts]"- Check for: publications, talks, media mentions
duckduckgo_search: "[Name] [key topic] site:medium.com OR site:dev.to OR site:substack.com"
-
Company-Specific Context:
duckduckgo_search: "[Name] [Company] announcement"- Look for: press releases, product launches, executive quotes
-
GitHub/Tech Presence (if technical role):
duckduckgo_search: "[Name] site:github.com"- Look for: open source contributions, personal projects
E. Parse Key Pages:
- Use
parse_webpage for high-value sources:
- Personal blog/website (if mentioned in any profile)
- Recent interviews or podcast appearances
- Conference speaker profiles
- Company "About Team" pages
- Notable Medium/Substack articles
- Popular Reddit AMAs or discussions
- Extract: bio, expertise areas, quotes, interests, unique perspectives
Platform Priority Strategy:
- Always analyze: LinkedIn (mandatory) + Web Search
- High priority: Twitter/X (if found) - usually most revealing for tech audience
- Medium priority: Reddit (if active) - shows technical depth and community engagement
- Low priority: Instagram - only if B2C focus or strong personal brand element
- Context-dependent: GitHub - critical for engineering roles, less for business roles
Cross-Platform Analysis:
- Compare tone across platforms (professional LinkedIn vs casual Twitter)
- Identify platform-specific content themes
- Note engagement levels per platform
- Synthesize consistent interests vs platform-specific behavior
Phase 5: Cross-Platform Strategic Analysis & Report Generation
Connection Strategy:
-
Conversation Topics (ranked by relevance, synthesized across all platforms):
- Top 3-5 topics from their LinkedIn posts/comments
- Hot takes or strong opinions from Twitter/X
- Technical discussions from Reddit
- Industry trends they've engaged with across platforms
- Shared interests or connections (if any)
- Recent company achievements to acknowledge
-
Engagement Approach:
- Best channels: LinkedIn comment, Twitter reply, Reddit comment, DM, email
- Channel preference: Note where they're most active/responsive
- Timing: based on posting patterns per platform (e.g., "most active on Twitter evenings, LinkedIn Tuesday mornings")
- Ice-breakers: reference specific post/comment/tweet that relates to AnySite
- Platform-specific tone: professional LinkedIn vs casual Twitter vs technical Reddit
-
Cross-Platform Personality Synthesis:
- Professional persona (LinkedIn) vs Personal persona (Twitter/Reddit)
- Technical depth indicators (Reddit discussions, GitHub activity)
- Communication style differences per platform
- Authentic interests (topics mentioned across multiple platforms)
Value Assessment for AnySite:
Analyze fit across multiple dimensions:
A. Direct Business Value:
- Potential customer: Does their company match AnySite ICP?
- B2B SaaS, AI companies, data-intensive businesses
- Size indicators: 10-500 employees, growth stage
- Pain points: mentions of data extraction, API integrations, agent development
- Decision maker level: C-suite, VP, Director, Manager
- Budget authority indicators
B. Partnership Potential:
- Technology synergies (complementary tools/platforms)
- Channel partnership opportunities
- Integration possibilities
- Co-marketing potential
C. Network & Influence:
- Network size and quality (10k+ connections = super-connector)
- Industry influence (thought leader, frequent speaker)
- Investor connections (VC, angels in their network)
- Potential for introductions
D. Talent & Advisory:
- Expertise match for advisor/mentor role
- Potential hire for future scaling
- Domain knowledge that fills gaps
Prioritization Matrix:
- Tier 1 (Hot Lead): Decision maker + ICP match + high engagement
- Tier 2 (Warm Lead): Mid-level + ICP match OR influencer + relevant network
- Tier 3 (Long-term Nurture): Potential future value, build relationship
- Tier 4 (Low Priority): No clear fit, maintain basic connection
Output Format
Generate comprehensive markdown report with sections:
# Person Intelligence Report: [Name]
**Generated:** [Date]
**Analysis Depth:** [Quick/Standard/Deep]
**Confidence Score:** [0-100%] based on data availability
## Executive Summary
[2-3 sentences: who they are, what they do, why they matter to AnySite]
## Professional Profile
- **Current Role:** [Title] at [Company] (since [date])
- **Location:** [City, Country]
- **Experience:** [X years in industry/role]
- **Education:** [Degree, Institution]
- **Network Size:** [LinkedIn connections count]
- **LinkedIn Profile:** [URL]
- **Twitter/X:** [@handle or "Not found"] ([follower count if found])
- **Reddit:** [u/username or "Not found/searched"]
- **GitHub:** [username or "Not found"] (if technical role)
- **Personal Website:** [URL if found]
## Key Background
[2-3 paragraphs covering:]
- Career trajectory and notable positions
- Expertise and specializations
- Notable achievements or credentials
## Multi-Platform Activity Analysis
### LinkedIn Activity (Last 90 Days)
#### Content Themes
1. **[Theme 1]** (40% of posts)
- Key topics: [list]
- Example post: "[quote or summary]"
2. **[Theme 2]** (30% of posts)
- Key topics: [list]
3. **[Theme 3]** (20% of posts)
[X posts/month]
[Average likes, comments per post]
[Description]
[Topics they comment on most]
[count]
[count]
[total count]
[created date]
[tweets per day/week]
[% original tweets vs retweets vs replies]
[list top 3-5 themes]
[avg likes, retweets per tweet]
[any strong opinions or viral tweets]
[code snippets, technical discussions level]
[types of accounts: VCs, founders, engineers, etc.]
[professional/casual/humorous/technical]
[list top 3-5 subreddits]
[post/comment karma if visible]
[% asking questions vs answering vs discussions]
[level of detail in technical responses]
[helpful, expert, casual participant]
[any popular posts or helpful answers]
[professional characteristics]
[casual/personal characteristics]
[technical/community characteristics]
[topics/interests mentioned across platforms]
[which platform has highest activity]
[where they get most responses]
[professional insights on LinkedIn, hot takes on Twitter, deep tech on Reddit]
[Synthesized description: formal/casual, technical depth, storytelling approach, cross-platform consistency or variation]
[Sector]
[Employee count]
[Startup/Scale-up/Enterprise]
[Brief description]
[@handle or "Not found"] ([follower count if found])
[Active/Mentioned/Not found]
[Key developments from last 6 months]
[Hiring, funding, expansion signals]
[Brief competitive context]
[If relevant]
[Themes from company LinkedIn posts, strategic priorities]
[Followers, following, tweets]
[Product announcements, culture, technical content, engagement]
[Key tweets from last 30 days]
[tweets per week]
[avg likes, retweets]
[Hiring, funding, launches]
[Where company is discussed]
[Number of mentions found]
[Positive/Mixed/Negative - with examples]
[What users like]
[Pain points mentioned]
[What people ask about]
[Links to significant discussions]
[How company is viewed on social vs LinkedIn]
[Real feedback from Twitter/Reddit vs official messaging]
[Hiring activity, expansion mentions across platforms]
[Company values in practice vs stated]
[How they're compared to competitors on social]
[List if any]
[List if any]
[Medium, Substack, Dev.to, personal blog]
[Notable press mentions]
[Open source contributions, personal projects if technical]
[contribution level, popular repos]
[reputation, areas of expertise]
[blog posts, tutorials, documentation]
[Insights from parsed webpages, quotes, expertise areas, unique perspectives]
- [Why: specific post/tweet/comment from which platform]
- [Why: company context or cross-platform theme]
- [Why: shared interest/industry trend across platforms]
- [Why: technical interest from Reddit/GitHub]
- [Why: personal interest from Twitter]
[Best days/times based on activity]
[Professional, comment on specific post]
"[Example referencing their LinkedIn content]"
(if active):
[Best days/times]
[Casual reply to tweet, quote tweet with value-add]
"[Example referencing their tweet or discussion]"
(if active):
[When they're most active]
[Helpful comment in their frequented subreddit]
"[Technical question or insight in relevant subreddit]"
[Email/LinkedIn DM/Twitter DM - ranked by likelihood]
[Optimal day/time synthesized from all platforms]
[How to position AnySite relevance based on their interests]
[Inferred from their role, company, posts across platforms - where AnySite could help]
[Pain point 1 with evidence from platform]
[Pain point 2 with evidence from platform]
[Pain point 3 with evidence from platform]
[High/Medium/Low]
ICP Fit: [Yes/No - reasoning]
Decision Authority: [Level]
Buying Signals: [List any indicators]
[High/Medium/Low]
[Specific opportunities if any]
[High/Medium/Low]
[Influence level, connection value]
[High/Medium/Low]
[Specific expertise value]
[Critical/High/Medium/Low]
[Contact within: X days/weeks]
[Specific action item with reasoning]
[Follow-up action]
[Long-term nurture plan if applicable]
LinkedIn: [✓ Profile, Posts, Comments, Reactions]
Twitter/X: [✓ Found and analyzed / ✗ Not found / - Not searched]
Reddit: [✓ Activity found / ✗ No activity / - Not searched]
GitHub: [✓ Projects found / ✗ Not found / - Not applicable]
Web: [✓ Articles/interviews found]
[List specific tools used]
LinkedIn posts: [date range analyzed]
Twitter: [date range if analyzed]
Reddit: [date range if analyzed]
[approximate: X posts, Y tweets, Z comments analyzed]
Profile completeness: [High/Medium/Low]
Activity data: [High/Medium/Low - per platform]
External validation: [High/Medium/Low]
Cross-platform consistency: [High/Medium/Low]
[Any data gaps, platforms not accessible, or constraints]
Error Handling & Edge Cases
Insufficient Data:
- If posts/comments are minimal: focus more on company analysis and role-based inferences
- If profile is sparse: use web search more heavily
- If company is small/unknown: focus on person's expertise and network
Multiple Profile Matches:
- Always confirm with user before proceeding with deep analysis
- Present distinguishing factors clearly
Rate Limiting / API Errors:
- Continue with available data from other sources
- Note limitations in report
- Suggest manual verification steps
Privacy Considerations:
- Only analyze publicly available information
- No speculation on private/personal matters
- Focus on professional context
Customization Parameters
Users may request analysis depth adjustment:
Quick Analysis (10-15 min):
- LinkedIn: Profile + last 10 posts + company basics
- Company: LinkedIn company profile only
- Twitter/X: Person profile check only (if handle found)
- Web: 2-3 targeted searches
- Reddit/GitHub: Skip unless specifically requested
- Output: Essential info only
Standard Analysis (20-30 min) - DEFAULT:
- LinkedIn: Full profile + 20-50 posts + comments/reactions + company analysis
- Company: LinkedIn + Twitter account + Reddit mentions search (NEW)
- Twitter/X: Person profile + 50 recent tweets (if found)
- Reddit: Search for person username + activity (if found)
- Web: 5-7 strategic searches + parse 2-3 key pages
- GitHub: Quick check for presence (if technical role)
- Output: Full workflow as described above
Deep Dive (45-60 min):
- LinkedIn: Extended analysis (100+ posts), all activity types, detailed company research
- Company: LinkedIn + Twitter (30 posts) + Reddit (comprehensive mentions) + sentiment analysis (NEW)
- Twitter/X: Person 100+ tweets, thread analysis, engagement patterns (if found)
- Reddit: Person comprehensive comment history, subreddit analysis (if found)
- Web: 10-15 searches, parse 5-10 webpages, deep technical footprint
- GitHub: Detailed repo analysis, contribution patterns (if technical)
- Instagram: Profile and content analysis (if relevant)
- Output: Comprehensive cross-platform synthesis with deep insights
Platform-Specific Focus:
Users can also request focus on specific platforms:
- "Focus on Twitter presence" → Deep Twitter analysis for person AND company, standard LinkedIn
- "Technical profile only" → LinkedIn + GitHub + Reddit + Stack Overflow (person focused)
- "Business profile" → LinkedIn + web presence + media, skip Reddit/GitHub
- "Company deep dive" → Extended company social analysis across all platforms (NEW)
Default to Standard Analysis unless specified.
