Best AI skills for finance and ops teams
The best AI skills for finance and ops teams: close checklists, GL reconciliation, variance commentary, 13-week cash forecasts, and SaaS metrics.
By Type Team
What are the best AI skills for finance and ops teams?
The best AI skills for finance and ops teams are Month End Close Checklist, GL Reconciliation, Budget Variance Commentary, and Cash Runway Forecaster. They turn the close, bank and payout reconciliations, variance commentary, and the 13-week cash forecast into repeatable runs that reconcile to your own numbers and flag anything that does not tie.
An AI skill is a packaged set of instructions, scripts, and sample data that Claude or Codex follows the same way every time a task comes up. Nine of the ten skills below do the arithmetic in a bundled script rather than in the model's head, so the same exports produce the same numbers on every run.
Finance and ops work is recurring, rules-heavy, and unforgiving. The close runs every month, a bank rec has one right answer, and a wrong number in the board pack or the morning Slack post costs more than the hours it saved. Several of these skills check the result against a figure you supply, such as the bank balance, the P&L operating variance, or billing MRR, and fail the run instead of plugging a gap, so the number you publish is one you can defend.
To see how this fits a whole finance function, Type's finance and operations page shows a shared Space with Claude or Codex connected to your ERP, billing, spend management, and banking. Every skill below is published in the Type Skills Library, where you can read its files and sample data before you install it.
| Skill | Best for | What you get |
|---|---|---|
| Month End Close Checklist | Controllers running the daily close stand-up and the post-close retro | Projected vs target close day, critical path, blocked tasks, and a tie-out log with a verdict per account |
| GL Reconciliation | Accountants closing the bank rec or matching Stripe, PayPal, or Shopify Payments payouts | Matched items by stage, open items on each side, and a bridge to control totals that must tie to 0.00 |
| Budget Variance Commentary | FP&A and controllers preparing the monthly pack and budget-owner reviews | Material variances tagged volume, timing, permanent, or unclassified, plus draft commentary for owners to edit |
| Cash Runway Forecaster | Finance leads and founders refreshing the 13-week cash forecast for the board or lender | Weekly closing balances, runway in weeks, the first covenant breach, and collection or spend scenarios |
| Daily Revenue Check | DTC finance teams before the daily revenue number goes to Slack or leadership | One net-sales figure bridged to each channel, a PUBLISH or HOLD verdict, and a draft Slack message |
| Failed Payment Recovery | Finance and billing ops at subscription businesses working failed charges and dunning | Classified declines, a retry and email ladder with approval gates, every touch logged, and a weekly summary |
| SaaS Metrics Pack | SaaS finance teams preparing board packs, investor updates, and diligence answers | MRR waterfall, NRR, GRR, logo churn, quick ratio, ARPA, CAC, CAC payback, and the top movers |
| Promo Margin Guard | DTC finance leads and founders before and after a sale, code, or sitewide promo | Promo P&L by code, codes that lost money, breakeven discount depth per SKU, and an exclusion list |
| Inventory Stockout Risk | Ops and finance at DTC brands in the weekly purchasing and working capital review | Stockouts ranked by revenue at risk, reorder quantities and PO value by supplier, and overstock capital |
| Cohort LTV Analyzer | DTC finance and growth leads deciding whether paid acquisition pays back | Repeat rate, revenue and contribution-margin LTV triangles, CAC payback by cohort, and lagging cohorts |
Which AI skills should finance and ops teams use?
These ten skills cover the close, reconciliations, management reporting, cash, billing, and the unit economics that finance teams at B2B, SaaS, and DTC companies are asked to defend.
The list is ordered by where we suggest starting: the close and reconciliations first, then management reporting and cash, then revenue and billing checks, then SaaS and ecommerce unit economics. Six of the skills apply to both B2B and DTC businesses. Daily Revenue Check, Promo Margin Guard, Inventory Stockout Risk, and Cohort LTV Analyzer are built for DTC and ecommerce brands.
1. Month End Close Checklist
Month End Close Checklist sequences your close tasks by dependency, projects the close day against target, names the task blocking the critical path, and logs which balances tie to evidence.
A close slips when the task on the critical path stalls, and speeding up anything else does not move the date. This skill leads with projected versus target close and the next action on that path, and its tie-out log shows where each balance's evidence came from, which is the index an auditor asks for.
- Best for
- Controllers running the daily close stand-up and the post-close retro
- Works from
- Close task CSV (owners, dependencies, status) plus an optional tie-out CSV of GL vs evidence balances
- You get
- Projected vs target close day, critical path, blocked tasks, and a tie-out log with a verdict per account
2. GL Reconciliation
GL Reconciliation matches a bank statement or processor payout report to the general ledger by exact match, date tolerance, and many-to-one batches, then bridges every unmatched item back to the control totals.
A processor payout lands in the bank as one line while the GL holds the individual charges, which makes payout recs slow by hand. The batch stage matches those groups, and if the open items do not explain the whole difference, the skill exits with an error instead of plugging the gap.
- Best for
- Accountants closing the bank rec or matching Stripe, PayPal, or Shopify Payments payouts
- Works from
- Bank statement or processor payout CSV plus GL account detail from QuickBooks, Xero, or NetSuite
- You get
- Matched items by stage, open items on each side, and a bridge to control totals that must tie to 0.00
3. Budget Variance Commentary
Budget Variance Commentary compares actuals to budget by department and account, applies your materiality thresholds, classifies each material variance as volume, timing, or permanent where the data supports it, and drafts commentary.
Variance commentary usually means chasing budget owners for sentences at the end of a long close. This skill applies one materiality policy and drafts each sentence with the owner's name on it. When the data cannot support a cause, it marks the line unclassified and asks the owner rather than inventing one.
- Best for
- FP&A and controllers preparing the monthly pack and budget-owner reviews
- Works from
- Actuals vs budget CSV by department and account, with optional YTD, prior period, and unit drivers
- You get
- Material variances tagged volume, timing, permanent, or unclassified, plus draft commentary for owners to edit
4. Cash Runway Forecaster
Cash Runway Forecaster builds a 13-week direct cash forecast from your opening balance, AR and AP aging, payroll, and recurring commitments, then projects runway and the first week you break a minimum cash floor.
A runway figure built from cash divided by average burn rarely survives a lender's or board's questions. This skill schedules real receivables and payables week by week, tests your covenant, and models slipping collections or stretched payables, with a completeness check proving nothing in the input files was dropped.
- Best for
- Finance leads and founders refreshing the 13-week cash forecast for the board or lender
- Works from
- Cleared bank balance plus AR aging, AP aging, payroll schedule, and recurring commitments CSVs
- You get
- Weekly closing balances, runway in weeks, the first covenant breach, and collection or spend scenarios
5. Daily Revenue Check
Daily Revenue Check combines Shopify, Amazon, and wholesale invoices into one net-sales number using finance's revenue definitions, runs seven checks including freshness, duplicates, reconciliation, and late refunds, and returns PUBLISH or HOLD.
A wrong revenue number is hard to walk back once leadership has seen it. This skill uses only finance's definitions, removes Shopify copies of Amazon and wholesale orders, and holds the number when a feed is stale or a channel does not reconcile. It never posts anything; a person reviews and sends the draft.
- Best for
- DTC finance teams before the daily revenue number goes to Slack or leadership
- Works from
- Shopify, Amazon, and wholesale invoice exports, source report totals, and finance's revenue definitions
- You get
- One net-sales figure bridged to each channel, a PUBLISH or HOLD verdict, and a draft Slack message
6. Failed Payment Recovery
Failed Payment Recovery finds failed charges and past-due invoices, classifies each decline, and runs a retry and outreach ladder with approval gates, recording every touch so no customer is contacted twice.
Failed payments are churn nobody chose. Unlike the rest of this list, this skill acts: it retries charges and emails customers, so it asks you to confirm write access up front and, by default, holds every retry and send until you approve its first draft. It caps outreach at four touches per invoice, sends nothing in quiet hours, never retries hard or fraud declines, and offers no discount unless you allow one.
- Best for
- Finance and billing ops at subscription businesses working failed charges and dunning
- Works from
- A Stripe, Recharge, or Custom API billing connection with write access, plus an email send path
- You get
- Classified declines, a retry and email ladder with approval gates, every touch logged, and a weekly summary
7. SaaS Metrics Pack
SaaS Metrics Pack turns a subscription export into the full MRR waterfall (new, expansion, contraction, churn, reactivation) plus NRR, GRR, logo churn, quick ratio, ARPA, CAC, and CAC payback, and fails if it does not tie.
When a board member or diligence team asks how churn was calculated, a spreadsheet formula is a weak answer. This skill classifies every customer's movement, reconciles opening plus movements to closing exactly, and can check the result against your billing system's closing MRR.
- Best for
- SaaS finance teams preparing board packs, investor updates, and diligence answers
- Works from
- Subscription export with history from Stripe, Chargebee, Recurly, Paddle, or the GL, plus S&M spend
- You get
- MRR waterfall, NRR, GRR, logo churn, quick ratio, ARPA, CAC, CAC payback, and the top movers
8. Promo Margin Guard
Promo Margin Guard computes the true contribution margin of a discount after COGS, shipping, payment fees, refunds, and expected returns, names the codes that lost money, and solves the breakeven discount depth for every product.
A promotion's revenue shows up right away and its returns do not. This skill separates booked from expected margin, so a recent sale is not reported as profitable before returns land, and turns the 20% or 30% off question into a SKU exclusion list. It covers contribution margin only, not incrementality.
- Best for
- DTC finance leads and founders before and after a sale, code, or sitewide promo
- Works from
- Shopify promo orders and line items, plus landed unit cost and return rate per SKU
- You get
- Promo P&L by code, codes that lost money, breakeven discount depth per SKU, and an exclusion list
9. Inventory Stockout Risk
Inventory Stockout Risk computes days of cover per SKU from sales velocity, ranks imminent stockouts by revenue at risk, recommends reorder quantities against lead times, MOQ, and case pack, and sizes capital tied up in overstock.
For finance, inventory is cash on a shelf. This skill puts revenue at risk from stockouts next to working capital frozen in overstock and dead stock at landed cost, so you can see when the recommended PO value exceeds the capital sitting in slow stock.
- Best for
- Ops and finance at DTC brands in the weekly purchasing and working capital review
- Works from
- Sales history, an on-hand snapshot from Shopify or a 3PL or ERP, and supplier lead times, MOQ, and case pack
- You get
- Stockouts ranked by revenue at risk, reorder quantities and PO value by supplier, and overstock capital
10. Cohort LTV Analyzer
Cohort LTV Analyzer groups customers by first-order month and reports repeat rate, cumulative revenue and contribution-margin LTV at equal ages, CAC payback per cohort, and which cohorts trail a reference cohort.
A blended LTV number hides whether this quarter's customers are worth what January's were. This skill compares cohorts at the same age and measures payback against contribution margin, not revenue, which shows whether a weak cohort is a mix problem or a retention problem.
- Best for
- DTC finance and growth leads deciding whether paid acquisition pays back
- Works from
- Order export with a stable customer ID from Shopify, a warehouse, or an ERP, plus monthly marketing spend
- You get
- Repeat rate, revenue and contribution-margin LTV triangles, CAC payback by cohort, and lagging cohorts
How should finance and ops teams choose which AI skills to start with?
Start with the recurring task that has one right answer and a control total to prove it, usually the bank reconciliation or the close checklist, then add judgment-heavy work like variance commentary once the team trusts the output.
The best first skill is one where you already know what done looks like. A bank rec is done when the residual is 0.00, and a close's tie-outs are done when every account says tied. GL Reconciliation and Month End Close Checklist both print that verdict and exit with an error when it fails, so the first run shows quickly whether your exports are right.
Run the sample before your own data. Every script-based skill on this list ships sample files and an expected output, and its instructions say to run the example and match that output exactly before touching real numbers. Most samples also include a run that fails on purpose.
Then fix the inputs, not the tolerances. Most of these skills work from exports such as a trial balance, AR and AP aging, or a Shopify orders file, and the errors their instructions warn about most sit in the export: a flipped sign, mismatched date ranges, or a summary report where detail was needed. Give each skill one owner who knows the source system.
- Start with work that has a right answer: bank recs, tie-outs, and MRR roll-forwards.
- Run each skill's bundled sample first and confirm it matches the expected output.
- Name one owner per skill who knows the source export and its sign conventions.
- Supply the control total (bank balance, operating variance, billing MRR) on every run.
- Have a named person review drafted commentary and approve Failed Payment Recovery's first draft.
How do finance and ops teams run these skills together in Type?
In Type, finance and ops teams create a Space, connect their ERP, billing, and banking tools once, install skills from the library, and run them with Claude or Codex in Slack or the Type app, on demand or on a schedule.
A team can set up one Space for finance, or one per entity or business line. Tools are connected once and assigned to the Spaces that need them, with team and individual permissions controlling who can use what.
Install the skills you need from the Skills Library and run them in Slack or the Type desktop and mobile apps with Claude or Codex. Recurring work becomes an automation, such as a Monday Cash Runway Forecaster refresh or a Daily Revenue Check before the morning revenue post. When the controller adds a tie-out source or FP&A tightens a materiality threshold, the whole team gets the improvement.
See how a finance Space comes together on Type's finance and operations page, or browse the full set of skills in the Type Skills Library.
Frequently asked questions
What is an AI skill for finance teams?
An AI skill is a packaged set of instructions, often with scripts and sample data, that Claude or Codex follows the same way every time. For finance, that means a bank rec or cash forecast runs on the same rules and thresholds every month, whoever runs it. Finance skills like GL Reconciliation and SaaS Metrics Pack do the math in a bundled script and reconcile to a control total.
How is an AI skill different from a prompt?
A prompt is a one-off request, and the answer can shift with the wording. A skill packages the method: the inputs it expects, the checks it runs, the scripts it calls, and how to present the result. For finance work, that consistency is what makes a number repeatable and reviewable from one close to the next.
Do these finance skills work with Claude and Codex?
Yes. In Type, teams run skills with Claude or Codex using the subscriptions they already pay for. The skill packages are plain SKILL.md folders, so they also work in other agent environments that read SKILL.md, such as Claude Code and Codex.
Do these AI skills post journal entries or change our accounting system?
The close, reconciliation, reporting, and forecasting skills do not. Month End Close Checklist, GL Reconciliation, Budget Variance Commentary, Cash Runway Forecaster, and SaaS Metrics Pack read CSV files you export, and the close checklist and GL Reconciliation state outright that they do not post journals or write back to the GL. Failed Payment Recovery is the exception: it retries charges and emails customers, so it needs billing write access that you confirm, and by default it holds every retry and send until you approve its first draft and records each touch on the invoice or subscription.
Can we customize a finance skill for each entity?
Yes. Materiality thresholds, matching tolerances, the target close day, and the minimum cash balance are settings passed on each run, so each entity can use its own. The close, reconciliation, variance, cash, and SaaS metrics skills each work in one currency without consolidation, so a multi-entity group runs them one entity at a time.
Where can I find more AI skills for finance and ops teams?
The Type Skills Library at type.com/library/skills publishes each skill with its full package of files, including any scripts and sample data, so you can read exactly what it does before installing it. It includes skills for the close, reconciliations, cash forecasting, billing, and SaaS and ecommerce unit economics.