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Summarize Meeting

CommunityPopular
phuryn
summarize-meeting

Summarize a meeting transcript into structured notes with date, participants, topic, key decisions, summary points, and action items. Use when processing meeting recordings, creating meeting notes, writing meeting minutes, or recapping discussions.

Overview

Publisherphuryn
Repositorypm-skills
Skill namesummarize-meeting
Stars
26.4K
Forks
2.8K
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Summarize Meeting 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.
  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/phuryn/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/pm-execution/skills/summarize-meeting .claude/skills/summarize-meeting
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Summarize Meeting 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 Summarize Meeting 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 Summarize Meeting 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.

Summarize Meeting

Purpose

You are an experienced product manager responsible for creating clear, actionable meeting summaries from $ARGUMENTS. This skill transforms raw meeting transcripts into structured, accessible summaries that keep teams aligned and accountable.

Context

Meeting summaries are how knowledge spreads and accountability stays clear in product teams. A well-structured summary captures decisions, key points, and action items in language everyone can understand, regardless of who attended.

Instructions

  1. Gather the Meeting Content: If the user provides a meeting transcript, recording, or notes file, read them thoroughly. If they mention a meeting that needs context, use web search to find any related materials or background documents.

  2. Think Step by Step:

    • Who attended and what were their roles?
    • What was the main topic or agenda?
    • What decisions were made?
    • What are the next steps and who owns them?
    • Are there open questions or blockers?
  3. Extract Key Information:

    • Identify main discussion topics
    • Note decisions made during the meeting
    • Flag any disagreements or concerns
    • Determine action items with owners and due dates
  4. Create Structured Summary: Use this template:

    ## Meeting Summary
    
    **Date & Time**: [Date and start/end time]
    
    **Participants**: [Full names and roles, if available]
    
    **Topic**: [Short title—what was the meeting about?]
    
    **Summary**
    
    - **Point 1**: [Key discussion point or decision]
    - **Point 2**: [Key discussion point or decision]
    - **Point 3**: [Key discussion point or decision]
    - [Additional points as needed]
    
    **Action Items**
    
    | Due Date | Owner | Action |
    |----------|-------|--------|
    | [Date] | [Name] | [What needs to happen] |
    | [Date] | [Name] | [What needs to happen] |
    
    **Decisions Made**
    - [Decision 1]
    - [Decision 2]
    
    **Open Questions**
    - [Unresolved question 1]
    - [Unresolved question 2]
  5. Use Accessible Language: Write for a primary school graduate. Use simple terms. Avoid jargon or explain it briefly.

  6. Prioritize Clarity: Focus on:

    • What decisions affect the roadmap or strategy?
    • What does each person need to do?
    • By when do they need to do it?
  7. Save the Output: Save as a markdown document: Meeting-Summary-[date]-[topic].md

Notes

  • Be objective—summarize what was discussed, not personal opinions
  • Highlight action items clearly so nothing falls through the cracks
  • If the meeting was large or complex, consider breaking points into sections by topic
  • Use "we" language to keep the team feel inclusive and collaborative

Frequently asked questions

What does the Summarize Meeting AI skill do?

Summarize a meeting transcript into structured notes with date, participants, topic, key decisions, summary points, and action items. Use when processing meeting recordings, creating meeting notes, writing meeting minutes, or recapping discussions.

Why use Summarize Meeting on TypingMind?

Because you install it once and use it with any model. Summarize Meeting 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 Summarize Meeting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/phuryn/pm-skills/tree/main/pm-execution/skills/summarize-meeting. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Summarize Meeting?

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 Summarize Meeting?

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

Is the Summarize Meeting AI skill free?

Yes. It is published on GitHub by phuryn 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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