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AI agents for winning teams. Best-in-class prompts for Notetaker templates, Sourcing, Deep Research, Reports and MCP — ready to copy, paste, and adapt.

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Welcome

Recruiting is a context problem. Top teams are learning to engineer it.

Every hiring conversation is data — the richest, most honest signal your organisation has about the talent market, your candidates, and your own team. The best teams don't just store it. They mine it, learn from it, and get sharper with every conversation.

This library is how you do that.

Below are a range of prompts built by the Metaview team, to be utilised across the Metaview platform, helping you re-engineer your hiring with real-life data at the core.

→ Find the prompt you want to use → copy it from its code block → paste it into Metaview → swap in your own details → uncover signal you can act on.

What's inside

Table of Contents

Section What it's for
Prompting Guide Extracting useful insights starts with good prompting. Before diving into each section, learn the fundamentals of what makes a great prompt.
1. Notetaker Structured note templates for screens, debriefs, kick-offs & coaching.
2. Sourcing Natural-language prompts to find candidates and companies.
3. Sequences Build world-class candidate outreach, that is personalised and genuinely unique to each candidate, at scale.
4. Deep Research Long-form research: market maps, talent intel, competitor benchmarking and more.
5. Reports AI columns that extract structured signal at scale.
6. MCP Level-up ways to add automation and insights within your hiring processes.

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Placeholders: Anywhere you see [Company], [role], [your name], or {COMPANY_NAME}, swap in your own details before running. Where a prompt references an attached document, upload your JD / competency framework / scorecard with the transcript.

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What is a prompt?

A prompt is a written instruction that tells the AI what to extract from your transcript, how to evaluate it, and how to format the result. Think of it like briefing a very fast, very literal junior teammate — the more precise you are, the better the output.

The six core prompting principles

  1. Be specific. Ask how, what, and with what result — not yes/no questions. The AI defaults to the broadest interpretation, so specifics minimise hallucination.
  2. Assign a role. Tell the AI who it is — e.g. "Act as a senior technical recruiter." It frames everything that follows.
  3. Specify your sources. Metaview can pull context from several places, so be explicit — e.g. "Refer to both the transcript and the job description."