froggo-mission-control: Skill for Claude Code

.claude/skills/financial-model/SKILL.md

financial-model is a skill for Claude Code from ProfFroggo/froggo-mission-control. It costs 29 tokens per session (938 once invoked), scanned A, original, Apache-2.0.

Process for building financial models, budget analyses, cost-benefit comparisons, and revenue forecasts — from raw data to structured financial output.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: positional $N argument.

This is ProfFroggo/froggo-mission-control's own configuration. It tells Claude Code how to work on froggo-mission-control itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything froggo-mission-control configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ProfFroggo/froggo-mission-control. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ProfFroggo/froggo-mission-control/dev/.claude/skills/financial-model/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ProfFroggo/froggo-mission-control

Made for: Claude Code.

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README.md
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Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 938 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00029 $0.00938
Opus 5.5 $0.00012 $0.00375
Sonnet 5.5 $0.00006 $0.00188
Haiku 4.5 $0.00003 $0.00094

Measured today against content hash 2e0cd1ca368a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

financial-model 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 today.

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.

.claude/skills/financial-model/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Financial Model

Purpose

Produce rigorous, assumption-transparent financial analyses. Every model must show its inputs, assumptions, and reasoning — conclusions without traceable data are not acceptable.

Trigger Conditions

Load this skill when:

  • Building or updating a budget (monthly, quarterly, annual)
  • Analyzing a spend request or cost-benefit decision
  • Forecasting revenue, runway, or unit economics
  • Comparing subscription costs or vendor pricing
  • Generating a financial report for mission-control or the owner

Procedure

Step 1 — Define the Question

State clearly:

  • What financial question is being answered?
  • What decision will this analysis inform?
  • What time horizon applies (monthly, quarterly, annual, multi-year)?

Step 2 — Identify Data Sources

List all inputs needed:

  • Existing budget files (check library/docs/research/ for prior finance reports)
  • Known fixed costs (subscriptions, tooling, headcount)
  • Variable costs (usage-based APIs, campaign spend)
  • Revenue or income data if applicable

Never invent numbers. If a data point is missing, flag it as an assumption with a range estimate.

Step 3 — Structure the Model

Use this standard layout for any model:

INPUTS (facts and confirmed data)
├── Revenue: ...
├── Fixed costs: ...
└── Variable costs: ...

ASSUMPTIONS (estimates with rationale)
├── Growth rate: X% — based on [source/rationale]
└── Churn rate: Y% — based on [source/rationale]

CALCULATIONS
├── Gross margin: Revenue − COGS
├── Operating expenses: Fixed + Variable
└── Net: Gross margin − OpEx

OUTPUTS
├── Monthly burn rate
├── Runway (months)
└── ROI or payback period (if applicable)

Step 4 — Run Scenarios

For any recommendation, produce 3 scenarios:

  • Conservative: Pessimistic assumptions (worst-case inputs)
  • Base: Most likely assumptions
  • Optimistic: Best-case inputs

Label each scenario clearly. Never present only the base case.

Step 5 — Validate

Before finalizing:

  • Do totals add up? Verify arithmetic.
  • Are all assumptions explicitly stated and defensible?
  • Are currency, units, and time periods consistent throughout?
  • Flag any input that has >20% uncertainty as HIGH RISK.

Read the full file on GitHub · 134 lines

Changes

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.

  1. today First seen · 134 lines · 29 tokens per session scan A 2e0cd1ca368a

Subscribe to this mod's changes

financial-model is a skill published in the GitHub repository ProfFroggo/froggo-mission-control (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 938 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-11-07.

Related

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