Universal Deep Search

Comprehensive intelligence gathering across ALL available data sources with cascading analysis.

Core Principle: CASCADING SEARCH

Every search expands to related entities:

PERSON → + their company + key colleagues + company news
COMPANY → + founders + C-level team + investors + competitors mentions
TOPIC → + key people mentioned + companies involved + YC startups in space

Query Classification

Type 1: PERSON

Triggers: Names, roles ("CEO of"), profile URLs, "who is", "find person"

Context to extract:

Full name (required)
Company (helpful)
Role/title (helpful)
Location (helpful)

Type 2: COMPANY

Triggers: Company names, domains (.io, .com), "startup", "company", linkedin.com/company/

Context to extract:

Company name (required)
Domain (helpful)
Industry (helpful)
Location (helpful)

Type 3: TOPIC

Triggers: Abstract concepts, questions, hashtags, "news about", "trends in"

Context to extract:

Keywords (required)
Time frame (helpful)
Industry/niche (helpful)

PERSON Search Workflow

Phase 1: Find & Identify Person

1. search_linkedin_users
   - keywords: "[name]"
   - company_keywords: "[company]" if known
   - title: "[role]" if known
   - count: 10

2. If multiple matches → present top 5 for confirmation
3. If YC founder suspected → search_yc_founders(query="[name]")

Phase 2: Deep Profile Analysis

1. get_linkedin_profile
   - user: "[username or URL]"
   - with_experience: true
   - with_education: true
   - with_skills: true
   
   CRITICAL: Extract and save:
   - Full URN: urn:li:fsd_profile:ACoAAA...
   - Current company slug/URN
   - Current role & start date

2. get_linkedin_user_posts
   - urn: "[full URN from above]"
   - count: 50
   
3. get_linkedin_user_comments
   - urn: "[full URN]"
   - count: 30

4. get_linkedin_user_reactions
   - urn: "[full URN]"
   - count: 50

Phase 3: Cross-Platform Presence

1. search_twitter_users
   - query: "[name] [company]"
   - count: 5
   
2. get_twitter_user (if found)
   - user: "[handle]"

3. get_twitter_user_posts
   - user: "[handle]"
   - count: 100

4. search_reddit_posts
   - query: "[name] OR [username]"
   - count: 20

5. get_instagram_user (if B2C/personal brand)
   - username: "[handle]"

6. duckduckgo_search
   - query: "[name] [company] speaker OR interview OR article OR podcast"
   - count: 10

7. duckduckgo_search
   - query: "[name] site:github.com OR site:medium.com OR site:substack.com"
   - count: 10

Phase 4: CASCADE → Company Analysis

Always analyze person's current company:

1. get_linkedin_company
   - company: "[company slug from profile]"

2. get_linkedin_company_posts
   - urn: "[company URN]"
   - count: 20

3. parse_webpage
   - url: "[company website]"
   - only_main_content: true

4. parse_webpage
   - url: "[company website]/about"

5. search_yc_companies (check if YC company)
   - query: "[company name]"

6. duckduckgo_search
   - query: "[company] funding news 2024 2025"
   - count: 10

Phase 5: CASCADE → Key Colleagues

1. get_linkedin_company_employees
   - companies: ["[company slug]"]
   - keywords: "founder OR CEO OR CTO OR VP"
   - count: 10

2. For top 2-3 executives:
   - get_linkedin_profile (brief)

COMPANY Search Workflow

Phase 1: Find & Identify Company

1. search_linkedin_companies
   - keywords: "[company name]"
   - location: "[location]" if known
   - industry: "[industry]" if known
   - count: 10

2. search_yc_companies
   - query: "[company name]"
   - hits_per_page: 20

3. If multiple matches → present options for confirmation

Phase 2: Deep Company Profile

1. get_linkedin_company
   - company: "[slug]"
   
   Extract: URN, employee count, industry, description

2. get_linkedin_company_employee_stats
   - urn: "[company URN]"

3. get_linkedin_company_posts
   - urn: "[company URN]"
   - count: 30

Phase 3: Website Intelligence

1. parse_webpage (homepage)
   - url: "https://[domain]"
   - only_main_content: true
   - extract_contacts: true

2. parse_webpage (about)
   - url: "https://[domain]/about"

3. parse_webpage (pricing)
   - url: "https://[domain]/pricing"

4. parse_webpage (team/leadership)
   - url: "https://[domain]/team" OR "/about#team"

5. get_sitemap
   - url: "https://[domain]/sitemap.xml"
   - count: 50

Phase 4: Social & Community Presence

1. search_twitter_users
   - query: "[company name]"
   - count: 5

2. get_twitter_user
   - user: "[company handle]"

3. get_twitter_user_posts
   - user: "[handle]"
   - count: 50

4. search_twitter_posts
   - query: "[company] OR @[handle]"
   - count: 100

5. search_reddit_posts
   - query: "[company name]"
   - count: 50

6. search_reddit_posts
   - query: "[company name]"
   - subreddit: "[relevant sub]" (e.g., "startups", "SaaS", industry-specific)
   - count: 30

7. search_instagram_posts (if B2C)
   - query: "#[company] OR [company name]"
   - count: 20

Phase 5: CASCADE → Leadership Team Analysis

Always analyze founders and C-level:

1. get_linkedin_company_employees
   - companies: ["[slug]"]
   - keywords: "founder"
   - count: 10

2. get_linkedin_company_employees
   - companies: ["[slug]"]
   - keywords: "CEO OR CTO OR CPO OR CFO OR COO"
   - count: 10

3. For each founder/C-level (top 5):
   a. get_linkedin_profile
      - with_experience: true
      - with_education: true
      - with_skills: true
   
   b. get_linkedin_user_posts
      - count: 20
   
   c. search_twitter_users → get_twitter_user_posts
      - count: 30

4. search_yc_founders
   - query: "[founder names]"

Phase 6: News & External Intelligence

1. duckduckgo_search
   - query: "[company] funding news"
   - count: 10

2. duckduckgo_search
   - query: "[company] launch product announcement"
   - count: 10

3. duckduckgo_search
   - query: "[company] review OR competitor OR alternative"
   - count: 10

4. parse_webpage (top news articles)
   - Parse 3-5 most relevant results

5. If tech company:
   duckduckgo_search
   - query: "[company] site:github.com"
   - count: 5

Phase 7: Y Combinator Check

1. search_yc_companies
   - query: "[company name]"

2. If found:
   get_yc_company
   - company: "[slug]"
   
   Extract: batch, status, funding, team size, founders

3. search_yc_founders
   - query: "[company name]"

TOPIC Search Workflow

Phase 1: Web Overview

1. duckduckgo_search
   - query: "[topic keywords]"
   - count: 15

2. duckduckgo_search
   - query: "[topic] trends 2024 2025"
   - count: 10

3. duckduckgo_search
   - query: "[topic] news recent"
   - count: 10

4. parse_webpage
   - Parse top 5 most authoritative results

Phase 2: Professional Discussion (LinkedIn)

1. search_linkedin_posts
   - keywords: "[topic]"
   - count: 30

2. search_linkedin_companies
   - keywords: "[topic] OR [related terms]"
   - count: 20

3. search_linkedin_users
   - keywords: "[topic] expert OR thought leader"
   - count: 10

Phase 3: Real-time Sentiment (Twitter)

1. search_twitter_posts
   - query: "[topic]"
   - count: 100

2. search_twitter_posts
   - query: "[topic] #[hashtag]"
   - count: 50

3. search_twitter_users
   - query: "[topic] expert"
   - count: 10

Phase 4: Community Insights (Reddit)

1. search_reddit_posts
   - query: "[topic]"
   - count: 50

2. search_reddit_posts
   - query: "[topic]"
   - subreddit: "[most relevant sub]"
   - count: 30

3. get_reddit_post_comments (on popular posts)
   - Parse top 3 most discussed threads

Phase 5: Visual Content (Instagram)

1. search_instagram_posts
   - query: "#[topic_hashtag]"
   - count: 20

Phase 6: Startup Landscape (Y Combinator)

1. search_yc_companies
   - query: "[topic]"
   - industries: ["[related industry]"]
   - hits_per_page: 50

2. For top 5 relevant YC companies:
   get_yc_company
   - company: "[slug]"

3. search_yc_founders
   - query: "[topic]"
   - industries: ["[related industry]"]

Phase 7: CASCADE → Key Entities

Identify and analyze key people/companies mentioned:

1. From all collected data, extract:
   - Most mentioned people → run PERSON mini-analysis
   - Most mentioned companies → run COMPANY mini-analysis

2. Mini-analysis (for each top entity):
   - LinkedIn profile/company
   - Recent posts
   - Twitter presence

Validation & Cross-Referencing

For PERSON

Name matches across platforms
Company/role consistency
Profile photo verification (same person)
Timeline consistency (career progression)

For COMPANY

Domain matches LinkedIn company
Employee count consistency
Founding date alignment
Industry classification match

For TOPIC

Source authority ranking
Recency weighting
Cross-source fact verification
Sentiment consistency

Confidence Scoring

HIGH: 4+ validation points, consistent across 3+ platforms
MEDIUM: 2-3 validation points, minor inconsistencies
LOW: 1 validation point or significant conflicts

Output Format

# Deep Search Report: [Subject]

**Type:** PERSON / COMPANY / TOPIC
**Query:** [Original query]
**Confidence:** HIGH / MEDIUM / LOW
**Platforms Searched:** [list all]
**Total API Calls:** [number]
**Analysis Date:** [date]

---

## Executive Summary

[3-5 key findings in bullet points]

---

## Primary Subject Analysis

### [Subject Name]

[Detailed findings organized by data type]

**Profile:**
[Core facts]

**Activity Analysis:**
[Posts, engagement patterns]

**Cross-Platform Presence:**
[Twitter, Reddit, Instagram, Web findings]

---

## Cascaded Analysis

### [Related Entity 1: Company/Person]
[Key findings from cascade]

### [Related Entity 2: Leadership/Colleagues]
[Key findings from cascade]

---

## Topic/Industry Context

[For PERSON/COMPANY: industry context]
[For TOPIC: full analysis here]

### YC Landscape
[Relevant YC companies and founders]

### Recent News & Trends
[From web search]

---

## Cross-Platform Synthesis

**Consistent Facts:**
- [Facts verified across multiple sources]

**Platform-Specific Insights:**
- LinkedIn: [professional persona]
- Twitter: [public opinions]
- Reddit: [community engagement]
- Instagram: [personal brand]

**Inconsistencies/Flags:**
- [Any conflicts to note]

---

## Sources

| # | Platform | URL | Type | Freshness |
|---|----------|-----|------|-----------|
| 1 | LinkedIn | [link] | Profile | Current |
| 2 | Twitter | [link] | Posts | Last 30d |
| 3 | Reddit | [link] | Discussion | Last 7d |
| 4 | YC | [link] | Company | Current |
| 5 | Web | [link] | Article | [date] |

---

## Metadata

- Platforms: LinkedIn, Twitter, Reddit, Instagram, YC, Web
- Data Points Collected: ~[number]
- Validation Status: PASSED / PARTIAL / NEEDS_REVIEW
- Cascade Depth: [how many related entities analyzed]

Quick Reference: All Endpoints Used

LinkedIn (24 tools)

search_linkedin_users - find people
search_linkedin_companies - find companies
search_linkedin_sales_navigator_users - advanced people search
get_linkedin_profile - person details
get_linkedin_company - company details
get_linkedin_company_employees - team members
get_linkedin_company_posts - company content
get_linkedin_company_employee_stats - growth data
get_linkedin_user_posts - person's posts
get_linkedin_user_comments - person's comments
get_linkedin_user_reactions - person's reactions
search_linkedin_posts - topic search

Twitter (5 tools)

search_twitter_users - find accounts
get_twitter_user - profile details
get_twitter_user_posts - tweets
search_twitter_posts - topic/mention search

Instagram (8 tools)

get_instagram_user - profile
get_instagram_user_posts - posts
search_instagram_posts - hashtag/topic search
get_instagram_user_friendships - followers/following

Reddit (3 tools)

search_reddit_posts - find discussions
get_reddit_post - post details
get_reddit_post_comments - comments

Y Combinator (3 tools)

search_yc_companies - find startups
get_yc_company - company details
search_yc_founders - find founders

Web (3 tools)

duckduckgo_search - web search
parse_webpage - extract content
get_sitemap - discover pages

Error Handling

No results: Try alternative spellings, broader terms, different platforms Rate limits: Continue with available data, note gaps Private profiles: Note as limitation, use public data Multiple matches: Present options, ask for confirmation

Search Depth Options

User can request:

Quick scan (10 min): Primary endpoints only, no cascade
Standard (20-30 min): Full workflow, 1-level cascade (DEFAULT)
Deep dive (45-60 min): Extended counts, 2-level cascade, all platforms

universal-search

Universal Deep Search

Core Principle: CASCADING SEARCH

Query Classification

Type 1: PERSON

Type 2: COMPANY

Type 3: TOPIC

PERSON Search Workflow

Phase 1: Find & Identify Person

Phase 2: Deep Profile Analysis

Phase 3: Cross-Platform Presence

Phase 4: CASCADE → Company Analysis

Phase 5: CASCADE → Key Colleagues

COMPANY Search Workflow

Phase 1: Find & Identify Company

Phase 2: Deep Company Profile

Phase 3: Website Intelligence

Phase 4: Social & Community Presence

Phase 5: CASCADE → Leadership Team Analysis

Phase 6: News & External Intelligence

Phase 7: Y Combinator Check

TOPIC Search Workflow

Phase 1: Web Overview

Phase 2: Professional Discussion (LinkedIn)

Phase 3: Real-time Sentiment (Twitter)

Phase 4: Community Insights (Reddit)

Phase 5: Visual Content (Instagram)

Phase 6: Startup Landscape (Y Combinator)

Phase 7: CASCADE → Key Entities

Validation & Cross-Referencing

For PERSON

For COMPANY

For TOPIC

Confidence Scoring

Output Format

Quick Reference: All Endpoints Used

LinkedIn (24 tools)

Twitter (5 tools)

Instagram (8 tools)

Reddit (3 tools)

Y Combinator (3 tools)

Web (3 tools)

Error Handling

Search Depth Options