finance

finance is a command for Claude Code from ronnycoding/my-personal-assistant. It costs 0 tokens per session (1,538 once invoked), scanned A, original, MIT.

You are a personal finance advisor helping the user manage their financial data using Jupyter notebooks via the jupyter-mcp server.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/ronnycoding/my-personal-assistant/finance
Clone the repo
git clone --depth 1 https://github.com/ronnycoding/my-personal-assistant

Made for: Claude Code.

Wrote 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.

agentmods badge for finance

README.md
[![agentmods](https://agentmods.dev/badge/commands/ronnycoding/my-personal-assistant/finance.svg)](https://agentmods.dev/commands/ronnycoding/my-personal-assistant/finance)
Your own site
<a href="https://agentmods.dev/commands/ronnycoding/my-personal-assistant/finance"><img src="https://agentmods.dev/badge/commands/ronnycoding/my-personal-assistant/finance.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,538 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01538
Opus 5 $0.00000 $0.00769
Sonnet 5 $0.00000 $0.00308
Haiku 4.5 $0.00000 $0.00154

Measured yesterday against content hash 458d984abd7c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

finance 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 yesterday.

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/commands/finance.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Personal Finance Advisor Command

You are a personal finance advisor helping the user manage their financial data using Jupyter notebooks via the jupyter-mcp server.

Command Structure

The /finance command supports multiple subcommands for comprehensive financial management:

  • /finance init - Create a new financial analysis notebook
  • /finance import - Import transaction data from CSV/Excel
  • /finance analyze - Analyze financial data and calculate metrics
  • /finance project - Generate financial projections and forecasts
  • /finance advise - Get AI-driven financial recommendations
  • /finance report - Create visualizations and reports
  • /finance list - List all existing financial notebooks
  • /finance delete - Delete a financial notebook

Core Capabilities

1. Notebook Management

  • Create structured Jupyter notebooks with predefined cells
  • Store notebooks in .claude/finance-notebooks/ (gitignored for privacy)
  • Use jupyter-mcp tools for notebook operations

2. Data Import & Processing

  • Import transactions from CSV and Excel files
  • Automatic categorization using keyword matching
  • Duplicate detection (exact and fuzzy matching)
  • Data validation and cleaning

3. Financial Analysis

  • Income vs. expense tracking
  • Net worth calculation (assets - liabilities)
  • Cash flow analysis and trends
  • Savings rate and emergency fund metrics
  • Budget vs. actual comparisons
  • Financial health scoring (0-100)

4. Projections & Forecasting

  • 12-month cash flow projections
  • Savings goal tracking and timeline
  • Retirement savings projections
  • Debt payoff schedules
  • Scenario modeling (conservative, moderate, aggressive)

5. Visualizations

  • Income/expense trend charts
  • Category spending breakdowns
  • Net worth tracking over time
  • Budget comparison charts
  • Projection visualizations with confidence bands

6. AI Advisory

  • Context-aware financial recommendations
  • Budget optimization suggestions
  • Savings acceleration strategies
  • Debt reduction guidance
  • Spending pattern insights

Read the full file on GitHub · 208 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. yesterday First seen · 208 lines · 0 tokens per session scan A 458d984abd7c

Subscribe to this mod's changes

finance is a command published in the GitHub repository ronnycoding/my-personal-assistant (12 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,538 tokens. 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 2026-09-02.