anysite-competitor-intelligence

What this skill does

# anysite Competitor Intelligence

Comprehensive competitive intelligence gathering using anysite MCP server. Track competitors across LinkedIn, social media, and the web to understand their strategies, monitor their activities, and identify competitive opportunities.

## Overview

The anysite Competitor Intelligence skill helps you:
- **Track competitor companies** on LinkedIn and Y Combinator
- **Monitor hiring patterns** to identify growth areas and strategic priorities
- **Analyze content strategies** across social platforms
- **Benchmark positioning** and messaging
- **Identify key employees** and leadership changes
- **Track competitive movements** like funding, launches, partnerships

This skill provides 90% coverage of competitive intelligence capabilities with excellent LinkedIn and social media monitoring.

## v2 Tool Interface

All data fetching uses the universal `execute()` meta-tool:

```
execute(source, category, endpoint, params) → returns data + cache_key
```

After fetching, use these for analysis and export:
- `get_page(cache_key, offset, limit)` — paginate through large result sets
- `query_cache(cache_key, conditions, sort_by, aggregate, group_by)` — filter/sort/aggregate cached data without re-fetching
- `export_data(cache_key, format)` — export to CSV, JSON, or JSONL for sharing

Always call `discover(source, category)` first if unsure about endpoint names or params.

**Error handling**: Check response for `llm_hint` field on errors — it provides actionable guidance (e.g., "Likely passed fsd_company URN instead of company: prefix").

## Supported Platforms

- **LinkedIn** (Primary): Company pages, employee search, post monitoring, job listings, growth tracking
- **Y Combinator**: Startup competitor research, funding data, batch analysis
- **Twitter/X**: Social presence monitoring, content strategy, engagement analysis
- **Reddit**: Community sentiment, product discussions, competitor mentions
- **Instagram**: Brand presence, visual content strategy, influencer partnerships
- **YouTube**: Video content, channel growth, community engagement
- **Web Scraping**: Company websites, press releases, blog content
- **SEC**: Public company filings for competitors

## Quick Start

### Step 1: Identify Competitors

Choose your competitor identification method:

| Goal | v2 Call | Output |
|------|---------|--------|
| Find similar companies | `execute("linkedin", "search", "search_companies", {"keywords": "...", "count": 50})` | Company list with metrics |
| Research startup competitors | `execute("yc", "search", "search_companies", {"query": "...", "count": 50})` | YC startups by industry/batch |
| Discover by employee search | `execute("linkedin", "search", "search_users", {...})` → extract companies | Companies from employee profiles |
| Find by keywords/industry | `execute("linkedin", "search", "search_companies", {"keywords": "...", "industry": "...", "count": 50})` | Filtered company list |

### Step 2: Gather Competitive Intelligence

Execute MCP tools to collect competitor data:

**Company Profile Analysis**
```
execute("linkedin", "company", "company", {"company": "competitor-name"})
→ Returns: Description, size, location, website, specialties, URN
```

**Employee Intelligence**
```
execute("linkedin", "search", "search_users", {
  "company_keywords": "Competitor Inc",
  "title": "VP OR Director OR Head",
  "count": 50
})
→ Returns: Key employees, org structure insights
→ Use get_page(cache_key, 10, 50) to load more results
```

**Hiring Velocity Analysis**
```
execute("linkedin", "company", "company_employee_stats", {
  "urn": {"type": "company", "value": "<company_id>"}
})
→ Returns: Growth metrics, department distribution
→ Use query_cache(cache_key, sort_by=[{"field": "count", "order": "desc"}]) to rank departments
```

**Content Strategy**
```
execute("linkedin", "company", "company_posts", {
  "urn": {"type": "company", "value": "<company_id>"},
  "count": 20
})
→ Returns: Recent posts, engagement, messaging themes
→ Use query_cache(cache_key, aggregate=[{"field": "reactions", "function": "avg"}]) for engagement stats
```

### Step 3: Process and Analyze

Analyze gathered data for:
- **Growth signals**: Hiring velocity, funding, expansion
- **Strategic priorities**: Department hiring, job postings, content themes
- **Market positioning**: Messaging, target audience, value props
- **Competitive threats**: New products, partnerships, key hires

Use `query_cache()` to filter and aggregate without re-fetching:
```
query_cache(cache_key, conditions=[{"field": "department", "operator": "contains", "value": "Engineering"}])
```

### Step 4: Format Output

**Chat Summary**: Competitive insights with key findings
**CSV Export**: `export_data(cache_key, "csv")` → Competitor comparison matrix
**JSON Export**: `export_data(cache_key, "json")` → Complete data for tracking over time

## Common Workflows

### Workflow 1: Comprehensive Competitor Profile

**Scenario**: Deep dive on a specific competitor

**Steps**:

1. **Company Overview**
```
execute("linkedin", "company", "company", {"company": "competitor"})
→ Size, industry, description, website, founding year
→ Save the URN (convert fsd_company to company: prefix for sub-endpoints)
```

2. **Leadership Team**
```
execute("linkedin", "search", "search_users", {
  "company_keywords": "Competitor Inc",
  "title": "C-level OR VP OR SVP OR President",
  "count": 50
})
→ C-suite and VP-level executives
→ Use get_page(cache_key, 10, 50) for more results
```

3. **Organizational Structure**
```
execute("linkedin", "company", "company_employee_stats", {
  "urn": {"type": "company", "value": "<company_id>"}
})
→ Total employees, growth rate, department breakdown

For each department:
  execute("linkedin", "search", "search_users", {
    "company_keywords": "Competitor Inc",
    "title": "<department_title>",
    "count": 50
  })
→ Team sizes, key roles
```

4. **Hiring Intelligence**
```
execute("linkedin", "search", "search_jobs", {"keywords": "Competitor Inc", "count": 50})
→ Open positions, hiring priorities, expansion areas
→ Use query_cache(cache_key, group_by="location") to see geographic expansion
```

5. **Content Strategy**
```
execute("linkedin", "company", "company_posts", {
  "urn": {"type": "company", "value": "<company_id>"},
  "count": 50
})
→ Posting frequency, themes, engagement levels

execute("twitter", "user", "user", {"user": "competitor"})
execute("twitter", "user", "user_posts", {"user": "competitor", "count": 50})
→ Social media presence and strategy
```

6. **Product/Market Intelligence**
```
execute("webparser", "parse", "parse", {"url": "https://competitor.com"})
→ Positioning, messaging, product offerings

execute("webparser", "parse", "parse", {"url": "https://competitor.com/blog"})
→ Content topics, thought leadership

execute("reddit", "search", "search_posts", {"query": "Competitor Inc", "count": 20})
→ Customer sentiment, product feedback
```

**Expected Output**:
- Complete company profile
- Leadership team roster (10-20 executives)
- Hiring velocity and priorities
- Content strategy analysis
- Product positioning insights
- Customer sentiment summary
- Use `export_data(cache_key, "csv")` to create downloadable competitor report

### Workflow 2: Competitive Landscape Mapping

**Scenario**: Map all competitors in your space

**Steps**:

1. **Identify Competitors**
```
execute("linkedin", "search", "search_companies", {
  "keywords": "<your industry keywords>",
  "industry": "<industry>",
  "employee_count": ["51-200", "201-500", "501-1000"],
  "count": 50
})
```

2. **Filter and Prioritize**
```
For each company:
  execute("linkedin", "company", "company", {"company": "<alias>"})
  → Review description for relevance
  → Check employee count and growth
  → Verify competitive overlap
```

3. **Categorize Competitors**
```
Direct: Same products, same market
Indirect: Similar products, different market
Potential: Adjacent space, could expand
```

4. **Size and Gro