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Using SeekOut MCP

Prompting Patterns

Six patterns for better answers, drawn from real early-customer wins. Use one or all — they compound.

1

Be specific.

Role, location, seniority, must-have skill. Senior data engineers in Austin with Snowflake beats find data engineers.

2

Name the index when it matters.

Add …in the GitHub index or …from our ATS pipeline when the data source matters. Removes ambiguity.

3

Push back when results look off.

The count looks low — try free-text keywords instead of titles. The AI re-strategizes. Don't accept a weak first answer.

4

Iterate, don't restart.

Each follow-up refines the prior result. Starting over loses the context the AI just built up.

5

Ask for the source.

Show me the queries you used. Audit-friendly, and you learn the patterns the AI reaches for.

6

Chain actions in one prompt.

Search, save, draft outreach, push to your ATS — all in one ask. Save the top 5 to a workspace, draft outreach for each, and show me before any send.