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 agentmods add skills/luizedupp/rememb/creating-financial-modelsnpx skills add LuizEduPP/Rememb --skill creating-financial-modelsgit clone --depth 1 https://github.com/LuizEduPP/RemembWrote 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/luizedupp/rememb/creating-financial-models)<a href="https://agentmods.dev/skills/luizedupp/rememb/creating-financial-models"><img src="https://agentmods.dev/badge/skills/luizedupp/rememb/creating-financial-models.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00044 | $0.01105 |
| Opus 5 | $0.00022 | $0.00553 |
| Sonnet 5 | $0.00009 | $0.00221 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
creating-financial-models 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 5d 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.
This is a copy
84% identical to creating-financial-models — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Financial Modeling Suite
A comprehensive financial modeling toolkit for investment analysis, valuation, and risk assessment using industry-standard methodologies.
Core Capabilities
1. Discounted Cash Flow (DCF) Analysis
- Build complete DCF models with multiple growth scenarios
- Calculate terminal values using perpetuity growth and exit multiple methods
- Determine weighted average cost of capital (WACC)
- Generate enterprise and equity valuations
2. Sensitivity Analysis
- Test key assumptions impact on valuation
- Create data tables for multiple variables
- Generate tornado charts for sensitivity ranking
- Identify critical value drivers
3. Monte Carlo Simulation
- Run thousands of scenarios with probability distributions
- Model uncertainty in key inputs
- Generate confidence intervals for valuations
- Calculate probability of achieving targets
4. Scenario Planning
- Build best/base/worst case scenarios
- Model different economic environments
- Test strategic alternatives
- Compare outcome probabilities
Input Requirements
For DCF Analysis
- Historical financial statements (3-5 years)
- Revenue growth assumptions
- Operating margin projections
- Capital expenditure forecasts
- Working capital requirements
- Terminal growth rate or exit multiple
- Discount rate components (risk-free rate, beta, market premium)
For Sensitivity Analysis
- Base case model
- Variable ranges to test
- Key metrics to track
For Monte Carlo Simulation
- Probability distributions for uncertain variables
- Correlation assumptions between variables
- Number of iterations (typically 1,000-10,000)
For Scenario Planning
- Scenario definitions and assumptions
- Probability weights for scenarios
- Key performance indicators to track
Output Formats
DCF Model Output
- Complete financial projections
- Free cash flow calculations
- Terminal value computation
- Enterprise and equity value summary
- Valuation multiples implied
- Excel workbook with full model
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.
- 5d ago First seen · 194 lines · 44 tokens per session scan A 0680d021520f
creating-financial-models is a skill published in the GitHub repository LuizEduPP/Rememb (4 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,105 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to creating-financial-models, differing in 24 lines, and is treated as a copy.
Other skills, from other repositories
finance-data
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Effective Memory
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recall
Recall this repository's OwnMem local memory before changing code, and keep it healthy. Use when a repository contains .ownmem/, when past debugging lessons could apply ("have we hit this before", "why is it done this way"), or when the user mentions ownmem, project memory, or recalling across sessions.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.
honcho-integration
Integrate Honcho memory into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, and accessing Honcho's representation.
honcho-memory
Concepts and strategy for using a connected Honcho as persistent memory of the user — the recall/record loop and session and peer design. Start here to understand how Honcho memory works, then connect — via a first-class integration for your environment if one exists (preferred), or raw MCP tools (covered here) or the…