What it does

Uses the Form 5500-derived bond data in Zywave market data to find undersized bonds, computes the shortfall with the formula shown, and puts your own clients first because that’s a service obligation before it’s a prospecting list.

What you get back

  • Clients and Prospects tabs with plan assets, bond value, required bond, shortfall
  • The attorney-reviewed ERISA bonding explainer

Example prompt

Add the skill to your AI client first, then paste this. Swap the bracketed bits, and the names and numbers, for your own.

Run a fidelity bond sweep across our benefits book and the Wisconsin market.

Source: Written for this skill by the R&D AI Experience team.

These buttons try to pre-fill the prompt for you. Open Claude launches the Claude Desktop app (it won't work if you only use Claude in a browser); Open ChatGPT pre-fills the web chat when the browser allows it. Neither is guaranteed, so both also copy the prompt to your clipboard as a fallback -- if the tool opens with an empty box, paste. Connect the Zywave MCP in that tool first, or the prompt has no Zywave data to work with.

More prompts like this: Discover new prospects, 15 more from the Zywave MCP Prompt Library, filterable by line of business.

What it needs from you

A few details from you. You supply the specifics in the prompt, company, state, size, dates.

Details to fill in when you run it:

  • A territory, or nothing for a client-only sweep

Clients first. The shortfall formula is in the workbook so anyone can check it. Live-evaluated Sep 2026. One limitation. The market-data bond filter is currently ignored server-side, so prospect sweeps scan a budgeted territory (about 1 in 8 employers scanned has a shortfall) rather than looking up a list; the client sweep is unaffected.

Guides exist for Claude, Microsoft Copilot, ChatGPT, and Google Gemini Enterprise. Custom integrations talk to the MCP server directly, so start from the MCP Apps reference for those.

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