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 WellApp-ai/Well --skill cash-flow-forecastgit clone --depth 1 https://github.com/WellApp-ai/WellWrote 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/wellapp-ai/well/cash-flow-forecast)<a href="https://agentmods.dev/skills/wellapp-ai/well/cash-flow-forecast"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/cash-flow-forecast/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/wellapp-ai/well/cash-flow-forecast"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/cash-flow-forecast.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.00499 |
| Opus 5 | $0.00027 | $0.00249 |
| Sonnet 5 | $0.00011 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
cash-flow-forecast 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 11d 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.
What it actually says
Cash-flow forecast from Well
A trustworthy forecast is grounded in what actually happened — invoices raised, cash collected, and observed days-to-pay — not in optimistic projections. Every forecast must state its time window and filters, and flag thin history explicitly.
Build it from booked + collected
- Discover the schema first (see
well:querying-well-data). - Starting position — current cash:
well_get_schema("account_balances")/accounts, sum the latest balance per account (note the currency). - Expected inflows (booked) — open
invoices(issued, unpaid) with their due dates and outstanding amounts. Adjust each due date by the customer's observed days-to-pay where history exists (derive from pastinvoices+ their settlingtransactions/invoice_transactions). - Expected outflows (booked) — received/payable
invoiceswith due dates; plus recurring outflows visible intransactionshistory (rent, payroll, subscriptions). - Project the balance forward per period (week or month): starting cash + expected inflows − expected outflows. Report the projected balance per period and the runway (the period the balance crosses zero, if any).
Rules
- State the window and filters behind the forecast (e.g. "next 13 weeks, EUR, excludes intra-account transfers"). A forecast without its assumptions is a vanity number.
- Flag thin history. If days-to-pay or recurring-outflow history is sparse (low n), say so — confidence is overstated on thin data.
- Distinguish booked (invoices/contracts that exist) from assumed (run-rate extrapolation), and label which is which.
- Don't sum across currencies without converting (see
exchange_rates).
Present it
A per-period table — opening balance, inflows, outflows, closing balance — the runway in plain terms ("≈ N weeks at current trajectory"), the stated window/filters, and an explicit confidence note when history is thin.
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.
- 11d ago First seen · 28 lines · 54 tokens per session scan A 702094ec6fe3
cash-flow-forecast is a skill published in the GitHub repository WellApp-ai/Well (341 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 499 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 2026-08-30.
Other skills, from other repositories
lemon-squeezy
Lemon Squeezy simplifies global tax compliance and recurring billing. The official @lemonsqueezy/lemonsqueezy.js SDK handles interactions cleanly.
paddle
Paddle acts as a Merchant of Record, meaning they handle sales tax (VAT, GST) calculations and remittance for you. Use the @paddle/paddle-node SDK to manage subscriptions and invoices.
plaid
Plaid connects users' bank accounts to apps. This skill focuses on Plaid Link flow and the plaid-node SDK to extract transaction data.
stripe
Stripe provides APIs for payment processing, billing, subscriptions, and financial management. This skill focuses on the Stripe Node.js and Python SDKs, emphasizing PCI-compliant flows like Checkout Sessions and Webhook signatures.
braintree
Braintree (by PayPal) provides enterprise payment processing accepting Credit Cards, PayPal, Venmo, Apple Pay, and Google Pay with PCI-compliant Hosted Fields and Drop-in UI.
dashboards
Use when creating or extending Costory dashboards, generating interesting FinOps overviews (suggestgroupby + suggestusagemetrics + text widgets), adding or replacing widgets, copying widgets between dashboards, editing dashboardContext (global filter / period / groupBy) via updatedashboard, or applying shared-context…