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Metaview AI Skills are optional add-ons, not built-in Metaview features: reusable workflows you install into your own AI assistant, giving it repeatable processes for preparing interviews, organizing debrief evidence, researching talent markets, launching roles, and supporting sourcing work. Your team adds each skill, can edit every part of it, and can remove it at any time. Unlike a one-off prompt, a skill defines a consistent process: what information to gather, which Metaview tools to use, which safeguards to follow, and how to structure the output.
Skills retrieve, organize, and synthesize the information available to you through Metaview. They support human judgment; they do not make hiring decisions or replace your review.

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How skills work

Ask naturally

Describe the outcome you need without building a complex prompt.

Follow a workflow

The skill gathers relevant context and follows a defined, reusable process.

Use Metaview context

The Metaview MCP retrieves the conversations and recruiting data available under your existing permissions.

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Before you begin

You will need:
  • A Metaview workspace
  • Access to the relevant conversations and recruiting data
  • The Metaview MCP connected to your AI assistant — see MCP Overview
  • An AI client that supports Skills or reusable project instructions
What a skill can retrieve depends on your Metaview permissions, workspace configuration, connected systems, and the information available in the underlying records.

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Install a skill

1

Connect Metaview

Connect the Metaview MCP using the options available in your Claude workspace.
2

Copy the skill

Open the skill page you want and copy the full SKILL.md contents from the Install this skill section.
3

Add the skill

Save it as a SKILL.md file and add it using the Skills or project configuration available in your Claude workspace.
4

Ask naturally

Request the outcome described by the skill — for example, “Prepare me for my interview with Priya.”
The exact installation steps and feature availability depend on your AI client, plan, and workspace settings.

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Available skills

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Works with the AI Notetaker

These skills use interviews and conversations already captured in Metaview. Some outputs also depend on scorecards, candidate records, or other connected data being available.

Interview Prep

Prepare a factual brief from previous interviews, notes, scorecards, and role context — covering what has already been discussed and what remains unknown.

Interview Debrief

Organize interview evidence by competency, surface agreements and contradictions, and prepare a structured pack for a human-led debrief.

Day-One Brief

Turn an accepted candidate’s interview history into onboarding context for their manager, including working preferences, goals, concerns, and commitments made during hiring.

Interviewer Coaching

Review interview technique against a defined framework and surface specific examples that can support private coaching or team-level training.

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Requires Reports

These skills work across larger sets of conversations and may require access to Reports, AI fields, or relevant workspace data.

Interview Intelligence

Extract and aggregate information explicitly discussed across interviews, calibrate the analysis on real examples, and present the results with appropriate context and limitations.

Role Launch

Turn an intake conversation into a draft role brief, interview plan, templates, search criteria, and tracking setup for your team to review and approve.

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Requires Sourcing

These skills use Sourcing, Application Review, or talent-market research capabilities.

Sourcing Copilot

Start and refine searches, review candidates against approved role criteria, and prepare provisional shortlists for human review before outreach or ATS actions.

Talent Research

Research talent pools, feeder companies, locations, compensation expectations, and market conditions, then combine external findings with relevant themes from your interviews.

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Choose the right skill

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Use skills responsibly

Review before acting. Skill outputs are drafts. Check important details against the source records before sharing them or using them in a hiring, outreach, or people decision.
Focus on evidence. Ask skills to retrieve what was said, organize examples, and identify unanswered questions. Apply your own judgment to what that evidence means.
Treat missing information as unknown. Interview records and public professional profiles may be incomplete. Do not treat an absent detail as evidence that a candidate lacks a qualification.

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Keep people in control

Skills can help prepare information and suggest next steps, but consequential actions remain human-led. In particular:
  • Do not use a skill to make a hiring decision or automatically reject a candidate.
  • Review provisional candidate notes before applying a verdict, sending outreach, updating an ATS, or adding someone to a sequence.
  • Confirm the role criteria and evaluation framework before comparing evidence.
  • Keep subjective ratings, overall recommendations, and final decisions with the responsible hiring team.
These principles mirror the guidance in Best practices for Notes and Best practices for Sourcing.

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Use factual, job-relevant criteria

Prefer prompts and output fields that focus on relevant experience, examples, requirements, and statements made during the process.

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Handle sensitive information carefully

Only include personal information where it is relevant, appropriate, and available through permitted sources.
  • Do not infer protected characteristics, personality traits, emotions, health information, family circumstances, or other sensitive attributes.
  • Refer to work authorization only where relevant to legitimate hiring logistics and based on information the candidate or authorized system provided.
  • Refer to compensation expectations or voluntarily disclosed compensation information, rather than implying that Metaview independently knows what a person is paid.
  • Exclude compensation and interviewer evaluations from onboarding briefs unless your organization has a separate, appropriate process for sharing that information.
  • Redact unrelated sensitive disclosures before sharing outputs more broadly.

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Calibrate aggregate analysis

When using Interview Intelligence or Talent Research:
  • Test extraction questions against a representative set of conversations before relying on aggregated results.
  • Distinguish information that was not discussed from a negative response.
  • Include sample size, time period, scope, and important data limitations alongside charts or conclusions.
  • Avoid presenting correlations or patterns as proof of causation.
  • Use aggregate or anonymized reporting where named individual data is not necessary.

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Example requests

“Prepare me for my interview with Priya. Summarize what has already been discussed, identify relevant unanswered questions, and cite the source conversations.”
“Organize the interview evidence for Amara by our approved competencies. Show supporting examples, contradictions, and unknowns without making the hiring decision.”
“Across interviews from the last quarter, summarize the reasons candidates explicitly gave for declining. Calibrate the extraction first and include the sample size and limitations.”
“Update the search criteria based on this feedback. Treat missing profile information as unknown, and show me the revised criteria before running the next search.”

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Frequently asked questions

No. A skill provides the reusable workflow, while your prompt tells the AI what you want it to do in the current conversation.
No. Skills can retrieve and organize evidence, compare it against criteria you provide, and prepare provisional outputs for review. Hiring decisions and recommendations remain with the responsible people in your organization.
Yes. Skills can be adapted to your organization’s processes, terminology, output formats, evaluation framework, and safeguards. Keep custom instructions factual, job-relevant, and human-reviewed.
A skill can only use information exposed through the Metaview MCP and available under your existing permissions. It cannot retrieve information that is not present or accessible to you.
Some workflows may support actions such as creating a search, updating a candidate record, or preparing an outreach handoff. Consequential actions should require your confirmation and remain subject to the permissions and controls of the connected system.
Scheduling and recurring delivery depend on the capabilities of your AI client and the connections available in your workspace. Installing a skill alone does not create a recurring automation.
Review the cited conversations, transcripts, recordings, scorecards, profiles, or reports used to generate it. Correct speaker labels and incomplete source data before relying on the output.

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Building your own workflows

Skills cover common workflows. For anything they don’t — or if you want to build a custom workflow on your own data — see MCP Use Cases & Workflows for prompting patterns and the Metaview-specific gotchas worth knowing before you start.

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You remain in control

Metaview Skills help you spend less time gathering and organizing information while keeping evaluation and action with your team. Review the evidence, correct errors or missing context, and decide what happens next.