Agent skill · marketing growth · onewave-ai
prospect-panel-simulator
Simulate a panel of your real prospects and buyers to pressure-test sales and marketing before it goes out — cold emails, pitch decks, landing pages, pricing pages, demo scripts, proposals. Each simulated prospect reacts in character, raises the objection they'd actually raise, and tells you whether they'd reply, book, or ghost. Use to de-risk outbound and messaging without burning real leads.
Why this skill is useful
Provides a structured simulation process for evaluating sales and marketing artifacts, which the AI wouldn't reliably generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-07-15. 242 stars on the source repository.
What this skill does
Prospect Panel Simulator Before you send the email, run the deck, or publish the pricing page — run it past the people who'd receive it. This skill simulates a panel of your actual prospects and reacts the way the market will: skeptical, busy, half-reading, comparing you to three other options. Where customer-panel-of-experts debates a business decision with existing customers, this skill stress-tests a sales or marketing artifact against people who don't know you yet and don't owe you a reply. What it pressure-tests Cold emails and full sequences (does it get a reply, or a delete?) Pitch decks and one-pagers (where do they check out?) Landing pages and pricing pages (what makes them bounce?) Demo scripts and discovery-call openers Proposals and SOWs (what gets pushed back on?) Step 0 — Assemble the prospect panel 1. Preferred: load personas from icp-deep-scanner output (personas/, icp-profile.md) and seat the buying committee — economic buyer, champion, blocker, and end user — since a cold artifact hits all of them differently. 2. If no library exists and tools are connected, run icp-deep-scanner (read-only) to ground the panel in real won/lost-deal data and real objection language. 3. Bootstrap from the user's description only as a last resort, labeled PROVISIONAL. Critically, model cold-state prospects: they have low context, low trust, and an alternative they already use. A simulated prospect who reads charitably is useless. Security Read-only connections. No sending, no writing to any tool. No real prospect names/emails in output — these are archetypes. Secrets stay in env vars. Step 1 — Take in the artifact Read exactly what will go out (paste, file, or URL via WebFetch). Note the channel and the moment: a cold email at 7am from an unknown sender is judged differently than a pricing page reached after a demo. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills onewave-ai/prospect-panel-simulator