| name | vc-analyst |
| description | Universal VC investor analysis and outreach agent. Analyzes any startup project, understands fundraising stage, identifies ideal investor profile, scores investors, detects portfolio conflicts, generates personalized outreach. Starts with discovery questions to understand the project. Triggers: "analyze investors", "find investors", "investor research", "fundraising help", "score investor", "/vc-analyst".
|
VC Investor Analyst
Universal agent for startup investor research and outreach.
Onboarding Flow (REQUIRED FIRST)
Before analyzing investors, gather project context. Use AskUserQuestion tool.
Step 1: Project Discovery
Ask user to provide:
- Company website - to fetch and analyze
- Pitch deck or materials - file path or link
- One-liner - what does the company do?
AskUserQuestion:
- "What's your company website?"
- "Do you have a pitch deck I can review? (path or link)"
- "In one sentence, what does your company do?"
Step 2: Fetch & Analyze Project
-
Website: Use mcp__anysite__parse_webpage(url=website) to understand:
- Product/service description
- Target market
- Key features
- Pricing (if visible)
-
Pitch deck: Use Read tool if local file, or WebFetch if link
-
Extract key info:
- Problem & Solution
- Market size (TAM/SAM/SOM)
- Business model
- Traction metrics
- Team background
- Competitive landscape
Step 3: Fundraising Context
Ask with AskUserQuestion:
questions:
- question: "What stage are you raising?"
header: "Stage"
options:
- label: "Pre-Seed ($250K-$1M)"
description: "First institutional round, idea to early product"
- label: "Seed ($1M-$3M)"
description: "Product-market fit exploration"
- label: "Series A ($5M-$15M)"
description: "Scaling proven model"
- label: "Other"
description: "Specify your round"
- question: "How much are you raising?"
header: "Amount"
options:
- label: "$500K or less"
- label: "$500K - $1M"
- label: "$1M - $2M"
- label: "$2M+"
- question: "What's your current traction?"
header: "Traction"
options:
- label: "Pre-revenue"
description: "Building product, no revenue yet"
- label: "Early revenue (<$10K MRR)"
description: "First paying customers"
- label: "$10K-$50K MRR"
description: "Growing customer base"
- label: "$50K+ MRR"
description: "Strong traction"
Step 4: Investor Preferences
Ask with AskUserQuestion:
questions:
- question: "What type of investors are you targeting?"
header: "Investor Type"
multiSelect: true
options:
- label: "Angel investors"
description: "Individual investors, $25K-$250K checks"
- label: "Micro VCs"
description: "Small funds, $100K-$500K checks"
- label: "Seed VCs"
description: "Institutional seed funds, $500K-$2M"
- label: "Strategic angels"
description: "Industry experts for advice + capital"
- question: "Geographic preference?"
header: "Location"
options:
- label: "US only"
- label: "US + Europe"
- label: "Global"
- label: "Specific region"
- question: "Any specific industries or themes they should focus on?"
header: "Thesis"
multiSelect: true
options:
- label: "B2B SaaS"
- label: "AI/ML"
- label: "Developer Tools"
- label: "Other (specify)"
Step 5: Build Investor Profile
After gathering info, create investor_criteria.json:
{
"company": {
"name": "...",
"website": "...",
"one_liner": "...",
"stage": "Pre-Seed",
"raising": "$1M",
"traction": "...",
"thesis_keywords": ["B2B SaaS", "AI", "..."]
},
"ideal_investor": {
"types": ["Angel", "Micro VC"],
"check_size": "$50K-$500K",
"stage_focus": ["Pre-Seed",
Save to data/investor_criteria.json for reference.
Investor Analysis Workflow
After onboarding, analyze investors from CSV or list.
1. Fetch LinkedIn Profile (ALWAYS FIRST)
mcp__anysite__get_linkedin_profile(user="linkedin-url-or-username")
CSV data has ~20% error rate. Always verify actual role before scoring.
2. Score Investor (0-100)
| Factor | Weight | Check |
|---|
| Is Actually Investor | GATE | Role: Partner, GP, Angel, EIR (NOT: Director, Manager, Engineer) |
| Stage Fit | 25% | Matches company's raising stage |
| Thesis Match | 25% | Matches company's thesis keywords |
| Portfolio Relevance | 30% | Similar companies in portfolio |
| Activity Level | 10% | Investments in last 12-18 months |
| Network Value | 10% | Accelerator ties, fund network |
Disqualifiers (Score = 0):
- Corporate role at non-investment firm
- Thesis mismatch (e.g., Crypto-only when company is SaaS)
- Wrong person at LinkedIn URL
- Stage too late (Series B+ fund for pre-seed company)
3. Check Portfolio Conflicts
Search for investments in company's competitors:
WebSearch("[Fund name] portfolio companies")
WebSearch("[Investor name] investments [competitor name]")
If conflict found: -20 points + flag "PORTFOLIO CONFLICT"
4. Generate Outreach Message
For Score > 70, create personalized message using company's outreach config:
Hi [Name],
[Hook from verified portfolio/achievement relevant to THIS company]
[1-2 sentences about company - from one_liner]
[Traction from company profile]
[Question based on their expertise]
Here's our pitch deck: [pitch_deck_link]
If you'd like to chat: [calendar_link]
If no slots work, send your availability.
Best,
[sender_name]
[sender_title]
Output Format
Per Investor
{
"investor": "Name",
"linkedin": "url",
"score": 85,
"current_role": "Partner @ Fund",
"stage_fit": "Pre-seed focus - MATCH",
"thesis_match": ["AI", "B2B SaaS"],
"portfolio_relevant": ["Company1", "Company2"],
"conflicts": [],
"risk_factors": [],
"outreach_hook": "Your investment in X...",
"message": "Full outreach text"
}
Batch Summary
{
"batch": 1,
"total_analyzed": 20,
"strong_fit": 4,
"good_fit": 3,
"not_fit": 13,
"top_candidates": ["Name1", "Name2"]
}
Quick Commands
| Command | Action |
|---|
/vc-analyst | Start full onboarding flow |
/vc-analyst analyze [linkedin] | Analyze single investor (requires prior onboarding) |
/vc-analyst batch [csv-path] | Analyze batch from CSV |
/vc-analyst update-criteria | Update investor criteria |
Scoring Reference
See references/scoring.md for detailed criteria and examples.
