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 commands/brainbytes-dev/everything-claude-finance/scenario-plangit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-financeWrote 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/commands/brainbytes-dev/everything-claude-finance/scenario-plan)<a href="https://agentmods.dev/commands/brainbytes-dev/everything-claude-finance/scenario-plan"><img src="https://agentmods.dev/badge/commands/brainbytes-dev/everything-claude-finance/scenario-plan.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 | $0.00009 | $0.01492 |
| Opus 5 | $0.00005 | $0.00746 |
| Sonnet 5 | $0.00002 | $0.00298 |
| Haiku 4.5 | $0.00001 | $0.00149 |
Grade A, and why
scenario-plan 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/scenario-plan — Financial Scenario Planning
What This Command Does
Builds structured financial scenario models with clearly defined assumptions, probability weightings, and decision trees. Compares outcomes across scenarios to support strategic decision-making. Identifies key variables that most influence outcomes and defines trigger points for scenario reassessment.
When to Use
- Strategic planning and board strategy sessions
- Market disruption response planning
- Investment decision analysis under uncertainty
- Risk management and contingency planning
- Capital allocation decisions
- Business continuity financial planning
How It Works
- Variable Identification: Maps key drivers that differ across scenarios
- Scenario Definition: Defines base, upside, and downside (or custom) scenarios with narrative
- Assumption Setting: Quantifies each driver per scenario
- Financial Modeling: Projects P&L, cash flow, and key metrics per scenario
- Probability Weighting: Assigns probabilities and calculates expected values
- Sensitivity Analysis: Identifies which variables have the largest impact on outcomes
- Decision Framework: Maps scenarios to strategic actions and trigger points
Example Usage
Input:
/scenario-plan topic:"European market expansion decision" scenarios:3 horizon:3-year
Output:
# Scenario Planning — European Market Expansion
## Decision: Enter DACH market via own subsidiary | Horizon: 2026–2028
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Scenario Definitions
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Scenario | Narrative | Probability |
|-----------|-----------------------------------------|-------------|
| Bull | Fast adoption, weak competition, strong EUR | 25% |
| Base | Steady growth, moderate competition | 50% |
| Bear | Slow adoption, price war, regulatory delays | 25% |
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Key Driver Assumptions
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Driver | Bull | Base | Bear |
|-------------------------|---------|---------|---------|
| Year 1 customers | 80 | 50 | 25 |
| Customer growth rate | 60%/yr | 40%/yr | 15%/yr |
| ARPU (EUR K/yr) | 45 | 40 | 35 |
| Sales cycle (months) | 3 | 5 | 8 |
| Customer churn | 8% | 12% | 20% |
| Gross margin | 75% | 70% | 62% |
| EUR/USD rate | 1.15 | 1.08 | 1.02 |
| Headcount needed (Yr 1) | 12 | 15 | 15 |
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Financial Projections by Scenario
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
### Bull Case (25% probability)
| EUR M | 2026 | 2027 | 2028 | Cumulative |
|----------------|--------|--------|--------|------------|
| Revenue | 2.7 | 6.8 | 14.2 | 23.7 |
| EBITDA | (1.5) | 1.2 | 5.1 | 4.8 |
| Cumulative CF | (3.2) | (2.5) | 1.8 | |
| Breakeven | | | Q2'28 | |
### Base Case (50% probability)
| EUR M | 2026 | 2027 | 2028 | Cumulative |
|----------------|--------|--------|--------|------------|
| Revenue | 1.5 | 3.8 | 7.5 | 12.8 |
| EBITDA | (2.2) | (0.8) | 1.8 | (1.2) |
| Cumulative CF | (3.8) | (5.0) | (3.8) | |
| Breakeven | | | Q4'28 | |
### Bear Case (25% probability)
| EUR M | 2026 | 2027 | 2028 | Cumulative |
|----------------|--------|--------|--------|------------|
| Revenue | 0.6 | 1.2 | 2.0 | 3.8 |
| EBITDA | (2.8) | (2.5) | (2.0) | (7.3) |
| Cumulative CF | (4.5) | (7.2) | (9.5) | |
| Breakeven | | | Not reached | |
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Expected Value & Decision Matrix
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Metric | Prob-Weighted Value | Risk |
|---------------------|---------------------|---------------|
| Expected NPV (3yr) | EUR (0.8M) | Marginal |
| Expected NPV (5yr) | EUR 4.2M | Positive |
| Max cash outlay | EUR 9.5M (bear) | Manageable |
| Probability of loss | 35% | Moderate |
### Decision: CONDITIONAL GO
Proceed if: (1) initial investment capped at EUR 5M, (2) 12-month review
gate at 30+ customers triggers full scale-up or exit, (3) partner
distribution model considered to reduce bear-case downside.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
## Trigger Points for Reassessment
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Trigger | Action if triggered |
|----------------------------|----------------------------------|
| < 20 customers by month 9 | Activate exit plan |
| > 60 customers by month 9 | Accelerate investment |
| Churn > 18% in any quarter | Pause expansion, fix product fit |
| Competitor enters at -30% | Reassess pricing strategy |
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.
- 4d ago First seen · 140 lines · 9 tokens per session scan A 701197263460
scenario-plan is a command published in the GitHub repository brainbytes-dev/everything-claude-finance (5 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 1,492 once invoked, about $0.0000 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 2026-08-31.
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