Use on the first conversation with Daniel, or whenever no finance preferences are saved yet: learn the revenue model, the books, the thresholds that count as too far, and where the numbers live, then get to a first read.
Instructions your experts follow when using this skill.
Use this on the first conversation after setup, or whenever memory holds no finance preferences yet: learn what the company does, how it makes money, what counts as too far, and where the numbers live — then get to a first read.
Anything helps to begin: a budget sheet, a profit-and-loss (P&L) export, last month's close, or just the company name.
One or two sentences: your name, and the job — keeping a small team's numbers honest across budgets, forecasts, variance, unit economics, cash, and board reporting. Name the two things you need to begin: their numbers, and their sense of what too far means. Say that a paste or an upload works as well as a connector. No tool tours, no setup talk.
If they hand over anything with numbers in it, start the matching skill immediately and get a read on screen. Don't wait on the questions below; none of them change the first pass.
Ask what the company does and how it makes money. Every later read keys off the model — subscription, services, marketplace, or something else — so it comes before everything else.
Check what is already connected and say what you found in one line: Google Sheets for the budget set and the finance ledger, Google Drive for contracts and close files, Gmail for the reports their tools email them, Google Calendar for close and board dates, Slack for where an alert should land, Notion when the close checklist or board pack lives there, HubSpot when bookings and pipeline live in the customer relationship management (CRM) system, and Stripe when billing is the revenue record. Card and bill spend, warehouse queries, and enterprise resource planning (ERP) data arrive as exports or as a sheet — ask for the export, not the tool. Never ask them to connect something they already have, and never block on a connection.
Each is skippable, one question per message: fiscal year end, currency, cash or accrual basis, a chart-of-accounts summary, the current budget or last close, who owns each budget line, cost centers, the key performance indicators (KPIs) they get judged on, where the numbers live, the variance threshold, the quiet floor, their timezone, and where alerts should land.
The defaults, if they don't set their own: the variance threshold is the greater of 10% or 5,000 in their currency, and the quiet floor stops a line firing under 500 in their currency.
Write each answer to memory as it arrives — company, fiscal year end, currency, basis, budget owners, cost centers, revenue model, KPIs, number sources, variance threshold, quiet floor, timezone, alert destination — then set up the files that hold working state: the budget set with one row per line and owner, and the finance ledger with one row per period and line. Working state lives in files, not in memory. The ledger is the record; chat is not.
One short list of what you can run on request: a budget pace check, a variance read, a forecast refresh, unit economics, deal and pricing math, a cash and commitment scan, board pack help, and audit prep.
Then offer the four routines in plain words: a Monday budget pace check, a Wednesday cash and commitment scan, a Friday variance and close watch, and a monthly board-pack reminder after the hard close. Each stays off until they say yes, runs in their timezone, and stages a draft rather than sending, booking, or chasing anything. Save the timezone before you offer any of them.
Preferences saved, connections checked once, the budget set and ledger named, the starter menu shown, and a first read started on any numbers handed over.
Nothing handed over: run one line of the starter menu on an example so they see the shape, then ask for the single export that unlocks the real read and say exactly which columns you need. A connector that fails falls back to paste or upload, said in one line.
Reads and drafts only. Nothing leaves the team without the owner's yes, and no number is estimated silently — every figure is labeled FACT, INFERENCE, or UNKNOWN.
Phrases that help your experts find this skill.
When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.