# Bayesian intrinsic growth valuation Human Guide

## What This Is For
Do not classify company news as simply bullish or bearish. It gives the agent a clearer input/output frame for growth marketing: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Bayesian intrinsic growth valuation agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for bayesian intrinsic growth valuation.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Bayesian intrinsic growth valuation guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- company fundamentals: revenue scale, margins, free cash flow, ROIC, balance sheet, customers, moat, pricing power
- industry cycle: demand growth, supply-demand gap, inventory cycle, order cycle, price trends, policy, downstream capex
- revenue and growth: historical growth, guidance, backlog, book-to-bill, organic growth, ASP, shipment volume
- TAM and TAM growth: current TAM, future TAM CAGR, penetration, market share, new market expansion
- valuation: EV/Sales, EV/EBITDA, P/E, FCF yield, PEG, historical percentile, peer percentile, implied growth
- share-price trend: 1M/3M/6M/12M and post-earnings returns, drawdown/rebound path, volatility, volume, relative performance versus sector/index, and whether price appreciation is ahead of intrinsic growth
- market FOMO: share-price move, options activity, social heat, analyst revisions, theme crowding, narrative strength
- new information: orders, customers, products, pricing, policy, competition, capacity, earnings, management guidance
- revenue history, gross margin, operating margin, EPS, free cash flow, capex, debt, cash, dilution, and share-count trends
- segment revenue, customer concentration, backlog/order language, risk-factor changes, and management's stated demand drivers
- 10-K and 10-Q trend baselines for the prior, and 8-K/earnings-release data for the latest update
- Form 4, 13D/G, and 13F data as sentiment/ownership context only, not as intrinsic-growth evidence by itself

## Decision Points And Nuance
The original skill emphasizes: Core Principle, Required Inputs, Optional SEC Data Assist, Growth Hypotheses, Workflow, Establish The Prior, Classify New Information By Variable, Bayesian Update, Calculate Weighted Intrinsic Growth, Reverse-Engineer Market-Implied Growth.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Prefer a conservative prior when evidence is incomplete. Do not let market excitement alone justify H4 or H5.
- If it looks cyclical, one-off, or backlog timing, avoid over-updating long-term growth.

## Copy-And-Paste Prompt
```text
Use the Bayesian intrinsic growth valuation human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the haskaomni/serenity-skill skill entry for `bayesian-intrinsic-growth-valuation`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Bayesian Intrinsic Growth Valuation

## Core Principle

Do not classify company news as simply bullish or bearish. Translate every company-specific data point into a probability update for future 3-5 year revenue growth, margin, TAM, market share, valuation multiple, and market sentiment.

The goal is to estimate the company's true intrinsic growth speed and compare it with the growth already implied by the current market value.

Treat outputs as research hypotheses, not personalized investment advice. Verify current market cap, price, revenue, margins, filings, guidance, peer multiples, and news from reliable current sources before making time-sensitive claims.

## Required Inputs

Use whatever the user provides, and clearly mark missing variables that require verification:

- company fundamentals: revenue scale, margins, free cash flow, ROIC, balance sheet, customers, moat, pricing power
- industry cycle: demand growth, supply-demand gap, inventory cycle, order cycle, price trends, policy, downstream capex
- revenue and growth: historical growth, guidance, backlog, book-to-bill, organic growth, ASP, shipment volume
- TAM and TAM growth: current TAM, future TAM CAGR, penetration, market share, new market expansion
- valuation: EV/Sales, EV/EBITDA, P/E, FCF yield, PEG, historical percentile, peer percentile, implied growth
- share-price trend: 1M/3M/6M/12M and post-earnings returns, drawdown/rebound path, volatility, volume, relative performance versus sector/index, and whether price appreciation is ahead of intrinsic growth
- market FOMO: share-price move, options activity, social heat, analyst revisions, theme crowding, narrative strength
- new information: orders, customers, products, pricing, policy, competition, capacity, earnings, management guidance

### Optional SEC Data Assist

For U.S.-listed companies, use SEC filings as the baseline evidence for reported historical fundamentals. `edgartools` can be used to fetch company filings, XBRL financial statements, filing text, insider transactions, ownership filings, and recent 8-K disclosures.

If the environment does not already have it, install with `pip install edgartools` or `uv pip install edgartools`. The import package is `edgar`, not `edgartools`. SEC access requires an identity; set `EDGAR_IDENTITY="Name email@example.com"` in the environment or call `from edgar import set_identity; set_identity("name@example.com")` before requests.

Minimal usage pattern:

```python
from edgar import Company

company = Company("AAPL")
financials = company.get_financials()
income = financials.income_statement()
balance = financials.balance_sheet()
cashflow = financials.cashflow_statement()
```

Use SEC data to anchor:

- revenue history, gross margin, operating margin, EPS, free cash flow, capex, debt, cash, dilution, and share-count trends
- segment revenue, customer concentration, backlog/order language, risk-factor changes, and management's stated demand drivers
- 10-K and 10-Q trend baselines for the prior, and 8-K/earnings-release data for the latest update
- Form 4, 13D/G, and 13F data as sentiment/ownership context only, not as intrinsic-growth evidence by itself

Do not use SEC data as a substitute for current market data, consensus estimates, forward multiples, TAM estimates, option activity, or real-time price movement. If using edgartools or SEC filings, name the form and filing date, and separate "reported fact" from "analyst/market estimate."

## Growth Hypotheses

Always frame future 3-5 year revenue CAGR as probabilities across these hypotheses:

| Hypothesis | Label | 3-5Y revenue CAGR |
| --- | --- | --- |
| H0 | contraction | <0% |
| H1 | mature slow growth | 0%-5% |
| H2 | steady growth | 5%-12% |
| H3 | high-cycle growth | 12%-25% |
| H4 | structural breakout | 25%-50% |
| H5 | platform expansion | >50% |

## Workflow

### 1. Establish The Prior

Assign initial probabilities to H0-H5 using fundamentals, industry cycle, TAM, historical growth, and competitive position.

Prefer a conservative prior when evidence is incomplete. Do not let market excitement alone justify H4 or H5.

### 2. Classify New Information By Variable

When new information appears, identify which variables it affects:

- revenue growth
- margin
- TAM
- market share
- competitive structure