fpa-learn-business

fpa-learn-business is a skill for Claude Code from JeffBrines/openfpa. It costs 56 tokens per session (1,088 once invoked), scanned A, original, MIT.

A workflow for documenting how a company operates before building its financial planning and analysis model. It creates a lasting business profile and can produce company-specific instructions when the standard workflows do not fit.

In plain words
What is it for?
Use it when onboarding a new company, setting up a model from scratch, or updating a missing or outdated business profile.
Why use it?
Forecasts depend on understanding the business behind the numbers. Recording that knowledge once gives later forecasting tasks a shared reference and avoids forcing every company into the same template.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the openfpa plugin — 14 skills shipped together

Good fit Use it when onboarding a new company, setting up a model from scratch, or updating a missing or outdated business profile.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jeffbrines/openfpa/fpa-learn-business
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.

Any agent
npx skills add JeffBrines/openfpa --skill fpa-learn-business
Clone the repo
git clone --depth 1 https://github.com/JeffBrines/openfpa

Made for: Claude Code.

Or install openfpa, the plugin that ships this one along with the rest of its 14 skills.

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 fpa-learn-business

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-learn-business/github.svg)](https://agentmods.dev/skills/jeffbrines/openfpa/fpa-learn-business)
Your own site
<a href="https://agentmods.dev/skills/jeffbrines/openfpa/fpa-learn-business"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-learn-business/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.

agentmods 80×15 button for fpa-learn-business

Your own site · 80×15
<a href="https://agentmods.dev/skills/jeffbrines/openfpa/fpa-learn-business"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-learn-business.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,088 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 $0.00056 $0.01088
Opus 5 $0.00028 $0.00544
Sonnet 5 $0.00011 $0.00218
Haiku 4.5 $0.00006 $0.00109

Measured 12d ago against content hash df82a7540d8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fpa-learn-business 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.

skills/fpa-learn-business/SKILL.md · 87 lines

How it starts

The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Learn the Business (Phase 0)

Overview

Before scaffolding any model, learn the business. This produces two artifacts: a durable business profile that every other openfpa skill reads first, and - where the standard skills don't fit - bespoke skills/agents generated for this specific company. The toolkit re-tools itself per business instead of forcing a generic template.

Core principle: A forecast is only as good as the business understanding behind it. Encode that understanding once, explicitly, so it grounds everything downstream.

When to use

  • A new company is being onboarded into openfpa
  • You're asked to "build us a model" / "understand our business" before forecasting
  • An existing .fpa/business-profile.md is missing or stale

Do not force this workflow when the user asks for a narrow task that can be completed without understanding the whole company.

Workflow

  1. Check and initialize the workspace. Run openfpa status <company-root>. If it is uninitialized, run openfpa init <company-root> --business-name "<name>". Then run openfpa doctor <company-root>. The CLI emits JSON. If the console script is unavailable in a source checkout, use python3 -m pyfpa.cli.

  2. Inspect local evidence first. Run openfpa inspect-data <data-root> for every user-supplied folder, then read the relevant financials, operating files, documentation, and existing model code before asking questions. Record each fact with openfpa intake-record <company-root>, including file references and confidence. Never access an external MCP/API system without the user's approval.

  3. Ask only what remains unknown. Run openfpa intake-next <company-root> and ask that related round of at most three questions. After every response, call openfpa intake-record with --source-type user. Direct answers are confirmed immediately. Only ask the user to resolve conflicting or low-confidence inferred facts.

  4. Repeat short rounds until pyfpa.intake_ready(intake) is true. Do not ask questions already answered by local evidence or earlier conversation.

Read the full file on GitHub · 87 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. 12d ago First seen · 87 lines · 56 tokens per session scan A df82a7540d8a

Subscribe to this mod's changes

fpa-learn-business is a skill published in the GitHub repository JeffBrines/openfpa (6 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 1,088 once invoked, about $0.0003 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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