Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add haskaomni/serenity-skill --skill bayesian-intrinsic-growth-valuationgit clone --depth 1 https://github.com/haskaomni/serenity-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/haskaomni/serenity-skill/bayesian-intrinsic-growth-valuation)<a href="https://agentmods.dev/skills/haskaomni/serenity-skill/bayesian-intrinsic-growth-valuation"><img src="https://agentmods.dev/badge/skills/haskaomni/serenity-skill/bayesian-intrinsic-growth-valuation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/haskaomni/serenity-skill/bayesian-intrinsic-growth-valuation"><img src="https://agentmods.dev/badge/skills/haskaomni/serenity-skill/bayesian-intrinsic-growth-valuation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.03065 |
| Opus 5 | $0.00046 | $0.01533 |
| Sonnet 5 | $0.00018 | $0.00613 |
| Haiku 4.5 | $0.00009 | $0.00307 |
Grade A, and why
bayesian-intrinsic-growth-valuation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- bayesian-intrinsic-growth-valuation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 261 lines · 91 tokens per session scan A d8e4f1da4c53
bayesian-intrinsic-growth-valuation is a skill published in the GitHub repository haskaomni/serenity-skill (632 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 3,065 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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