| name | earnings-viewer |
| description | Analyzes earnings calls + SEC filings, updates financial models, and drafts earnings notes. Use when user says "analyze earnings", "earnings call", "update model after earnings". |
| domain | financial |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | financial-analysis |
| tags | ["analysis","earnings","finance","investment","viewer"] |
| version | 1.0.0 |
Earnings Viewer
Persona
Earnings Analyst — Inspired by the earnings-reviewer agent from anthropics/financial-services. Combines transcript parsing, model updating, and note generation.
Core Philosophy: Earnings are the ultimate truth-telling moment. Every number, every tone shift, every guidance change reveals what management really thinks.
Overview
Automatically processes earnings calls and SEC filings to update financial models and draft analyst-quality earnings notes. Handles the full workflow: ingest → parse → model update → draft note.
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:
-
"earnings viewer"
-
"Earnings call just concluded (same day analysis)"
-
"10-Q/10-K filing published"
-
"Need to update DCF/LBO models with new data"
-
Earnings call just concluded (same day analysis)
-
10-Q/10-K filing published
-
Need to update DCF/LBO models with new data
-
Drafting earnings notes for investment committee
-
Comparing guidance vs. actuals across quarters
When NOT to Use:
- Pre-earnings scenario analysis (use
alphaear-strategy instead)
- General market research (use
trading/alphaear-strategy)
- Company initiation (use
research/mckinsey-research)
Implementation
The implementation follows a phased approach: ingest earnings data, update financial models, and draft analyst-quality notes.
Phase 1: Ingest & Parse
Supported Sources:
sources = {
"earnings_transcript": "https://.../Q3-2024-transcript.pdf",
"10q_filing": "https://.../10q.htm",
"guidance_letter": "internal memo",
"prior_notes": "Q1-Q2 notes for comparison"
}
Key Metrics Extraction:
earnings_data = {
"revenue": {"reported": 1.2e9, "guidance": 1.1e9, "beat": 0.1e9},
"ebitda": {"reported": 300e6, "margin": 0.25},
"eps": {"reported": 2.50, "consensus": 2.30, "beat": 0.20},
"guidance_change": "raised|maintained|lowered",
"key_quotes": ["We expect strong demand in Q4...", ...]
}
Phase 2: Model Update
DCF Model Update:
dcf_updates = {
"revenue_growth": update_forecast(new_growth_rate),
"ebitda_margin": adjust_margin(new_margin),
"capex": update_capex(new_capex_pct),
"wacc": recalc_wacc(new_beta, new_erp),
"terminal_value": update_tv(new_growth_assumptions)
}
LBO Model Update (if applicable):
lbo_updates = {
"entry_multiple": new_ev/ebitda,
"debt_schedule": update_amortization(new_cash_flow),
"covenant_headroom": check_covenants(new_ebitda),
"irr": recalc_irr(new_exit_multiple)
}
Phase 3: Earnings Note Draft
Template Structure:
# [TICKER] Q[X] 202[X] Earnings Note
## Headline
[Company] beats on [metric], raises guidance on [driver]
## Key Numbers
| Metric | Reported | Consensus | Variance |
|---------|----------|-----------|----------|
| Revenue | $X.XB | $X.XB | +X.X% |
| EPS | $X.XX | $X.XX | +X.X% |
## Management Commentary
- **Guidance:** [raised/maintained/lowered] for [metric]
- **Key Quote:** "[important quote]"
- **Strategic Shifts:** [new initiatives, pivots]
## Model Updates
- DCF: Revenue CAGR [X]% → [Y]%, PT $XX (was $XX)
- LBO: Entry multiple [X.X]x, IRR [XX]% (was [XX]%)
## Investment Thesis Impact
✅ **Strengthens:** [thesis point 1], [point 2]
⚠️ **Risks:** [new risk 1], [risk 2]
🎯 **Next Catalysts:** [event 1], [event 2]
Common Rationalizations
| Rationalization | Reality |
|---|
| "I'll update the model later" | Missed earnings = best time to update, while fresh |
| "Just note the headline numbers" | Model updates prevent circular reasoning later |
| "Management always beats, skip deep dive" | Guidance changes and tone shifts matter more than beats |
| "Earnings are boring, skip notes" | Earnings notes are the #1 most-referenced internal doc |
| "I'll draft tomorrow" | While memory is fresh = 2x faster, better quality |
Red Flags
- Model not updated within 24 hours of earnings
- Missing reconciliation: GAAP vs. Non-GAAP adjustments
- Copy-pasting transcript without synthesis
- Ignoring guidance changes (biggest forward signal)
- Note exceeds 3 pages (loses readability)
- No variance analysis: actuals vs. prior guidance
Verification
After completing an earnings analysis, confirm:
Integration Points
Cross-Skill References:
trading/alphaear-strategy — For pre-earnings scenario analysisfinancial/model-builder — For DCF/LBO model templatessales/high-ticket-closing — For presenting to investorsreferences/trading-checklist.md — For risk management validation
MCP Server Integrations:
- Morningstar MCP — For consensus estimates
- FactSet MCP — For peer comparison data
- S&P Global MCP — For sector benchmarking
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
