Meeting Analyzer logo

Meeting Analyzer

Organization
microsoft
meeting-analyzer

Analyzes meetings from pasted text, transcripts, or audio/video recordings and turns them into a structured intelligence report. Use this skill whenever the user shares meeting content in any form — a raw transcript, meeting notes, a Teams/Zoom recap, an audio or video file, or simply pastes a block of dialogue — and wants to understand what happened, who the participants are, what was decided, or "what really went on" in the meeting. Trigger it even when the user does not say "analyze": phrases like "summarize this meeting", "what did we agree on", "read this transcript", "insights from this call", or "what am I missing from this conversation" all indicate this skill. It surfaces explicit outcomes (decisions, action items, deadlines), builds persona profiles of the participants, and uncovers hidden insights: unspoken tensions, implicit risks, avoided topics, and signals that were never made explicit but matter deeply to the context.

Overview

Publishermicrosoft
Repositorycat-agent-skills
Skill namemeeting-analyzer
Stars
95
Forks
115
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Meeting Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/cat-agent-skills/tree/main/submissions/meeting-analyzer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/cat-agent-skills.git /tmp/cat-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cat-agent-skills/submissions/meeting-analyzer .claude/skills/meeting-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Meeting Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Meeting Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Meeting Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Meeting Analyzer

Act as a meeting-intelligence analyst. Produce evidence-grounded analysis, not a summary: surface what was decided, who the participants are behaviorally, and what was meant but not said.

Write the entire analysis in the language of the requesting user, regardless of the meeting's language. Keep direct quotes in their original language; add a translation when useful.

Step 1 — Ingest

  • Pasted text, transcript, or notes: use directly.
  • Audio or video: transcribe first with an available speech-to-text tool. If none is available, state that and ask the user to paste the transcript or captions. Do not infer content you cannot hear.
  • Assess source quality (verbatim vs. paraphrased, speakers labeled or not, gaps) and state it in the report. Scale the confidence of interpretive claims to source quality.
  • Ask at most one clarifying question, and only if the analysis cannot proceed without it; otherwise analyze and note assumptions.

Step 2 — Extract the explicit layer

Capture, with attribution:

  1. Purpose of the meeting and whether it was achieved.
  2. Decisions: who made each, and firmness (committed / leaning / discussed only). Do not upgrade a discussion into a decision.
  3. Action items: task, owner, deadline. Record missing owners/dates explicitly — they are findings.
  4. Key facts, figures, and constraints.
  5. Questions raised but not answered.

Step 3 — Build persona profiles

Read references/persona-framework.md, then profile each identifiable participant: apparent role and stake, communication style, positions and influence, and closest behavioral archetype. Ground every claim in something the person said or did. With unlabeled speakers, infer distinct voices only when the text clearly supports it, and mark the profile as inferred.

Step 4 — Uncover the hidden layer

Read references/hidden-insights-guide.md, then check every category: the unsaid, tension and subtext, fragile agreements, misalignments, power dynamics, unnamed risks.

For each insight provide: evidence (quote or moment), interpretation, and confidence (high / medium / low). Never present interpretation as fact. Cut insights that a neutral reader would not see in the evidence or that would change no action.

Step 5 — Deliver the report

Use the structure in assets/report-template.md. Keep the section order; scale depth to the material. End with 3–7 prioritized recommended next actions tied to specific findings, especially the hidden ones.

Quality bar

  • Every claim traces to evidence in the source material.
  • Hidden insights are clearly separated from explicit facts and carry confidence levels.
  • No invented names, dates, or commitments — gaps are reported as gaps.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Meeting Analyzer AI skill do?

Analyzes meetings from pasted text, transcripts, or audio/video recordings and turns them into a structured intelligence report. Use this skill whenever the user shares meeting content in any form — a raw transcript, meeting notes, a Teams/Zoom recap, an audio or video file, or simply pastes a block of dialogue — and wants to understand what happened, who the participants are, what was decided, or "what really went on" in the meeting. Trigger it even when the user does not say "analyze": phrases like "summarize this meeting", "what did we agree on", "read this transcript", "insights from th...

Why use Meeting Analyzer on TypingMind?

Because you install it once and use it with any model. Meeting Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Meeting Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/cat-agent-skills/tree/main/submissions/meeting-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Meeting Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Meeting Analyzer?

As many as you like. As long as a model supports skills, you can use Meeting Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Meeting Analyzer AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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