ICP Deep Scanner

ICP Deep Scanner

Turn the data already sitting in your connected tools into a rigorous, evidence-backed Ideal Customer Profile (ICP) and a library of buyer personas. Most ICPs are invented in a slide deck. This one is reverse-engineered from your actual best customers, your won/lost deals, your support tickets, and your reviews — then written so it can drive real decisions and feed the panel skills.

This skill is the data layer beneath customer-panel-of-experts, prospect-panel-simulator, and product-launch-war-room. Run it first; those skills read the persona library it writes.

Operating principles (read first)

• Read-only by default. You may query and read connected sources. You must NOT create, update, delete, send, or move anything in any connected tool unless the user explicitly asks in this session. Before any write or outbound action, stop and confirm.
• Least data necessary. Pull aggregates and representative samples, not entire databases. You are building a profile, not exfiltrating a CRM.
• PII minimization. Persona artifacts are archetypes, not dossiers. Do not write real customer names, emails, phone numbers, or account IDs into the output files. Reference real records only as anonymized counts and quotes (quotes scrubbed of identifying detail).
• Secrets via environment only. Never read, print, or write credentials. Assume tokens live in environment variables (e.g. $SUPABASE_TOKEN, $OPENAI_API_KEY) or in the MCP connection itself. If a source needs auth that isn't present, list it under "Sources I could not reach" and continue.
• Cite the evidence. Every claim in the ICP must trace to a source. "Buyers are mostly ops leaders" is worthless; "14 of the last 20 closed-won champions held an Operations title (CRM, trailing 12 mo)" is usable.

Step 1 — Inventory connectable sources

Ask the user which tools to scan, or detect what's available. Map each to what it tells you:

Present the list, mark which are reachable now, and confirm scope before scanning. For a wide scan across many sources, dispatch parallel read-only sub-agents (one per source) and merge their findings — see /agent-army.

Step 2 — Extract signal from each source

For each reachable source, pull:

• Firmographics — industry/vertical, company size, geography, business model, tech stack.
• Who buys — economic buyer, champion, blocker, end user (titles + seniority, from real deals).
• Why they buy — the trigger event, the job-to-be-done, the alternative they abandoned.
• Why they don't — top closed-lost reasons, top objections, top churn reasons.
• Language — the exact words customers use (mine reviews and tickets; do not paraphrase into marketing-speak).
• Economics — ACV, CAC signals, sales-cycle length, expansion behavior, concentration risk.