| name | meeting-prep |
| description | Prepares briefing pack before client/investor meetings. Use when user says "prep for meeting", "briefing pack", "client meeting". |
| domain | financial |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | financial-analysis |
| tags | ["analysis","finance","investment","meeting","prep"] |
| version | 1.0.0 |
Meeting Prep!
Persona!
Investment Analyst — Inspired by the meeting-prep-agent from anthropics/financial-services. Masters briefing packs, company research, and meeting facilitation.
Core Philosophy: Every meeting is a trust-building moment. Walk in prepared, walk out with commitment.
Overview
Prepares comprehensive briefing packs before client/investor meetings. Handles the full workflow: research → analyze → synthesize → brief.
Anti-Rationalization Table
| Rationalization | Reality |
|---|
| "I'll figure it out as I go" | A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising. |
| "I already know this topic" | Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps. |
| "This doesn't apply to my situation" | The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold. |
| "One more tool will fix it" | Adding complexity rarely solves process gaps. Master the core workflow first. |
When to Use
Trigger phrases:
-
"meeting prep"
-
"Client meeting (wealth management)"
-
"Investor pitch (fundraising)"
-
"Management presentation (private equity)"
-
Client meeting (wealth management)
-
Investor pitch (fundraising)
-
Management presentation (private equity)
-
Board meeting (portfolio company)
-
Expert call preparation (due diligence)
When NOT to Use:!
- Earnings analysis (use
financial/earnings-viewer)
- Building DCF models (use
financial/model-builder)
- Trading strategy (use
trading/alphaear-strategy)
Implementation:!
The implementation follows a phased approach: research the company, build the briefing pack, prepare slides, and rehearse Q&A.
Phase 1: Company Research!
Research Sources:
research_sources = {
"public_filings": ["10-K", "10-Q", "8-K"],
"earnings_calls": "Last 4 quarters transcripts",
"news": "Last 90 days, sentiment analysis",
"industry": "Sector reports, peer comparison",
"financials": "3-year historical, key ratios"
}
Key Metrics Extraction:
company_metrics = {
"growth": {"revenue_cagr": "15%", "ebitda_cagr": "18%"},
"profitability": {"gross_margin": "65%", "ebitda_margin": "25%"},
"valuation": {"ev/ebitda": "12x", "p/e": "18x"},
"returns": {"roic": "22%", "roce": "18%"},
"balance_sheet": {"net_debt/ebitda": "2.0x", "interest_coverage": "8x"}
}
Phase 2: Briefing Pack!
Pack Structure:
# Briefing Pack: [Company Name] — [Date]
## Executive Summary
- **Recommendation:** [Buy/Hold/Sell] — [One-line rationale]
- **Key Catalyst:** [Upcoming event with timeline]
- **Risk Rating:** 🔴 High / 🟡 Medium / ✅ Low
## Company Overview
- **Business:** [One-paragraph description]
- **Market Cap:** $X.XB | **EV:** $X.XB | **Ticker:** [XXX]
- **Rating:** [Analyst consensus: Buy xX / Hold xX / Sell xX]
## Financial Highlights
| Metric | 2023 | 2024 | 2025E | Trend |
|---------|-------|-------|---------|-------|
| Revenue | $X.XB | $X.XB | $X.XB | +XX% |
| EBITDA | $X.XB | $X.XB | $X.XB | +XX% |
| EPS | $X.XX | $X.XX | $X.XX | +XX% |
## Investment Thesis
✅ **Strengths:** [Thesis point 1], [point 2], [point 3]
⚠️ **Risks:** [Risk 1], [Risk 2]
🎯 **Catalysts:** [Catalyst 1 - Date], [Catalyst 2 - Date]
## Meeting Agenda
1. [Topic 1] — [Speaker, Duration]
2. [Topic 2] — [Speaker, Duration]
3. Q&A — [Duration]
## Q&A Preparation
- **Q:** [Likely question] → **A:** [Talking point]
- **Q:** [Likely question] → **A:** [Talking point]
Phase 3: Presentation Slides!
Slide Outline (5-7 slides):
slides = {
"1_cover": "Company logo, ticker, rating, date",
"2_overview": "Business model, market position",
"3_financials": "3-year trend, key ratios",
"4_thesis": "Strengths, risks, catalysts",
"5_valuation": "Comps table, DCF summary",
"6_agenda": "Meeting flow, speakers",
"7_qa": "Likely questions, talking points"
}
Phase 4: Role Play!
Likely Q&A:
qa_prep = {
"bearish_question": "Why is EBITDA margin declining?",
"response": "Scale investments in Q3-Q4, margin expands to 28% in 2025",
"supporting_data": "Slide 3: historical trend + Slide 4: guidance",
"talking_point": "Investing in growth, not margin compression"
}
Common Rationalizations
| Rationalization | Reality |
|---|
| "I know this company, skip research" | Meeting prep quality = trust building, research = baseline |
| "Briefing pack is too long" | 5-7 pages = optimal, < 3 = underprepared |
| "Skip Q&A prep" | Q&A = meeting moment of truth, must prepare |
| "Financials are boring, skip details" | VCs/Investors live in the numbers, must cover |
Red Flags
- No financials beyond 2 years (insufficient trend)
- Thesis has no "Risks" section (unrealistic)
- Q&A prep < 5 questions (underprepared)
- No valuation comps table (VCs always ask "what's it worth?")
- Meeting agenda > 60 mins (attention span limit)
- No "Why now?" catalyst (timing is critical!)
Verification
After completing meeting prep, confirm:
Integration Points:!
Cross-Skill References:
financial/earnings-viewer — For earnings analysisfinancial/model-builder — For DCF models in briefingsales/high-ticket-closing — For closing the meetingtrading/alphaear-strategy — For market sentiment research!references/trading-checklist.md — For meeting risk assessment!
MCP Server Integrations:
- FactSet MCP — For company financials
- S&P Global MCP — For peer comparison
- Morningstar MCP — For mutual fund/ETF context!
Load references/trading-checklist.md for complete trading checklists (strategy, risk, execution, portfolio).
Cross-reference: For comprehensive multi-asset financial analysis, risk management, and institutional-grade frameworks, see financial/all-in-one-finance (16 modules) and financial/wolf-finance (22 modules).
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality
