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 skills add JeffBrines/openfpa --skill fpa-configure-actualsgit clone --depth 1 https://github.com/JeffBrines/openfpaWrote 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/jeffbrines/openfpa/fpa-configure-actuals)<a href="https://agentmods.dev/skills/jeffbrines/openfpa/fpa-configure-actuals"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-configure-actuals/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.
<a href="https://agentmods.dev/skills/jeffbrines/openfpa/fpa-configure-actuals"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-configure-actuals.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00095 | $0.01036 |
| Opus 5 | $0.00048 | $0.00518 |
| Sonnet 5 | $0.00019 | $0.00207 |
| Haiku 4.5 | $0.00010 | $0.00104 |
Grade A, and why
fpa-configure-actuals scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Public filings** - a 10-K / 10-Q from SEC EDGAR (curl + a compliant User-Agent), as in the Fox Factory example. How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Configure Actuals & Data Sources (Phase 2)
Overview
Connect the model to real data - from wherever it lives. openfpa is not married to a connector: everything normalizes to one shape ({account: amount}), and where no built-in path exists, you build the ingestion for this source. That's the job, not a workaround - see examples/foxfactory/pull_edgar.py, a SEC-EDGAR adapter the agent wrote from scratch because no built-in one existed.
Core principle: one normalized shape regardless of source, so the engine never cares where the numbers came from - and the agent meets the data where it is.
The data can come from anywhere
- Local spreadsheets (always works, no credentials). A P&L, balance sheet, AR/AP aging, or inventory export.
pyfpa.read_pl_csv(path)reads any two-columnAccount, AmountCSV (handles$, commas,(parens)negatives) →{account: amount}- it is generic, not P&L-only. For richer tables (aged AR/AP buckets, item-level inventory) there is no rigid reader by design: parse the file to what the model needs - derive DSO from AR aging, DIO from inventory, DPO from AP aging. - A live accounting system via MCP - the cleanest live path. If a QuickBooks or NetSuite MCP server is connected, pull the trial balance / P&L / balance sheet through it and map the result to
{account: amount}. openfpa never handles credentials - the MCP server owns auth. - A live system via API - build a company-specific connector around the
source API and its actual report shape. The functions in
pyfpa.io.adaptersare fixture-backed examples only, not live QuickBooks, NetSuite, or Shopify clients. - Public filings - a 10-K / 10-Q from SEC EDGAR (curl + a compliant User-Agent), as in the Fox Factory example.
- Anything else - if the source isn't covered, write a small ingestion that returns
{account: amount}(or parses the richer statement to the drivers the model needs). That is the toolkit working exactly as intended.
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.
- 12d ago First seen · 59 lines · 95 tokens per session scan A 80c3f40a19de
fpa-configure-actuals is a skill published in the GitHub repository JeffBrines/openfpa (6 stars, last pushed 2mo ago), licensed MIT. It adds 95 tokens to every session and 1,036 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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