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Meeting Transcript

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huytieu
meeting-transcript

Process meeting recordings and notes into structured decisions, action items, and team dynamics with intelligent noise filtering

Overview

Publisherhuytieu
RepositoryCOG-second-brain
Skill namemeeting-transcript
Stars
1.2K
Forks
138
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 huytieu on GitHub. Read the source before you install it.

Installation

Install the Meeting Transcript 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/huytieu/COG-second-brain.git /tmp/COG-second-brain
mkdir -p .claude/skills
cp -r /tmp/COG-second-brain/skills/meeting-transcript .claude/skills/meeting-transcript
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Meeting Transcript 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 Transcript 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 Transcript 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.

COG Meeting Transcript Skill

When to Invoke

  • User shares a meeting transcript or recording notes
  • User says "process meeting", "meeting notes", "meeting transcript"
  • User has a block of text from a meeting they want structured
  • User mentions wanting to extract action items from a meeting

Agent Mode Awareness

Check agent_mode in 00-inbox/MY-PROFILE.md frontmatter:

  • If agent_mode: team — use the full parallel agent execution strategy below (3 agents)
  • If agent_mode: solo — process sequentially: extract content first, then analyze dynamics, then enrich with context.

Purpose

Extract strategic insights from meeting recordings and notes with intelligent content filtering to focus on substantive, actionable content while removing noise and irrelevant information.

Command: /meeting-transcript

Parallel Agent Team Execution Strategy

Use parallel agents to process different aspects of the transcript simultaneously.

Phase 1: Setup (Orchestrator)

  1. Receive transcript content from user
  2. Detect content type (meeting vs braindump) and classify domain
  3. Split transcript into logical sections for parallel processing

Phase 2: Parallel Processing (Spawn 2-3 Agents Simultaneously)

Launch ALL agents in a single message using Task tool with run_in_background: true:

Agent 1: "content-extractor" (subagent_type: general-purpose)
Extract structured content from the meeting transcript.

1. Filter out side chats, technical difficulties, and irrelevant banter
2. Identify and extract: decisions made (with rationale), action items (with owners/deadlines), strategic themes
3. Capture key quotes and insights from participants
4. Note unresolved issues and follow-up needs

Return: Decisions list, action items list, strategic themes, key quotes, unresolved issues.
Agent 2: "dynamics-analyst" (subagent_type: general-purpose)
Analyze team dynamics and meeting effectiveness.

1. Assess communication patterns and participation levels
2. Identify leadership moments and collaboration quality
3. Evaluate decision-making process effectiveness
4. Assess meeting efficiency (time well spent vs wasted)
5. Note any tensions, disagreements, or alignment issues

Return: Team dynamics assessment, participation analysis, meeting effectiveness score.
Agent 3: "context-enricher" (subagent_type: general-purpose)
Enrich meeting content with project/product context.

1. If project-related: read recent braindumps and notes for context
2. Check if discussed topics relate to known issues/PRs on GitHub
3. Connect decisions to existing strategic priorities
4. Identify competitive intelligence if competitors mentioned

Return: Contextual connections, related documents, strategic alignment notes.

Phase 3: Assembly (Orchestrator)

  1. Collect results from all processing agents
  2. Assemble structured meeting summary following Content Structure template
  3. Add proper metadata (participants, duration, type, action item count)
  4. Save to appropriate domain meeting folder
  5. Flag urgent action items for immediate attention

Content Filtering Guidelines

EXCLUDE (Filter Out)

  • Side Conversations: "Hey, did you see the game last night?"
  • Technical Difficulties: "Can you hear me now?" "Your mic is muted"
  • Incomplete Thoughts: "So I was thinking we should... never mind"
  • Casual Banter: Weather, personal anecdotes unrelated to work
  • Interruptions: "Sorry, I have to take this call"
  • Unclear Statements: Mumbled or inaudible content

INCLUDE (Keep and Analyze)

  • Strategic Discussions: Market analysis, competitive positioning
  • Decision Points: "We've decided to move forward with Option A"
  • Action Items: "Alex will complete the analysis by Friday"
  • Problem Solving: Discussion of challenges and proposed solutions
  • Planning: Timeline discussions, resource allocation
  • Insights: "The key insight is that customers want..."
  • Concerns: "My concern is that this approach might..."

Metadata Template

yaml
---
type: meeting-transcript
domain: [personal|professional|project-specific]
project: [project-name] # Only for project-specific meetings
date: YYYY-MM-DD
created: YYYY-MM-DD HH:MM
meeting_type: [1-on-1|team-meeting|strategic-planning|project-review|other]
participants: [participant1, participant2, participant3]
duration: [minutes]
content_filtered: true
accuracy_verified: [true|false|pending]
action_items_count: [number]
decisions_count: [number]
tags:
  - meeting
  - transcript
  - domain-tag
  - project-tag
status: [processed|needs-follow-up|action-required]
---

Content Structure

1. Meeting Overview

  • Date/Time: When the meeting occurred
  • Participants: Who was present and their roles
  • Purpose: Primary objective of the meeting
  • Duration: Actual meeting length
  • Type: Category of meeting

2. Key Decisions (Verified Content Only)

  • Decision: What was decided
  • Rationale: Why this decision was made
  • Owner: Who is responsible for implementation
  • Timeline: When decision takes effect
  • Impact: Expected outcomes and implications

3. Action Items (Substantive Only)

  • Task: Specific action to be taken
  • Owner: Person responsible
  • Deadline: When it's due
  • Dependencies: What needs to happen first
  • Success Criteria: How completion will be measured

4. Strategic Themes (From Substantial Discussion)

  • Theme: Major topic or pattern discussed
  • Context: Why this theme is important
  • Implications: What this means for the team/project
  • Next Steps: How to address or leverage this theme

5. Unresolved Issues

  • Issue: Problem or question that remains open
  • Context: Background and importance
  • Blocking Factors: What's preventing resolution
  • Proposed Next Steps: How to move forward

6. Team Dynamics Assessment

  • Communication Quality: How effectively team communicated
  • Decision-Making Process: How decisions were reached
  • Participation: Who contributed and how
  • Meeting Efficiency: Time management and focus
  • Areas for Improvement: Suggestions for better meetings

Domain-Specific Processing

Personal Domain Meetings

  • Focus on career development and personal growth
  • Maintain strict privacy for personal discussions
  • Extract learning and development opportunities
  • Save to [CUSTOMIZE: path/to/personal/]meetings/

Professional Domain Meetings

  • Analyze leadership and team management aspects
  • Extract strategic business insights
  • Identify professional development opportunities
  • Save to [CUSTOMIZE: path/to/professional/]meetings/

Project-Specific Meetings

  • Connect to project metrics and milestones
  • Analyze progress against project goals
  • Extract competitive and market intelligence
  • Save to [CUSTOMIZE: path/to/projects/][project-name]/meetings/

Content Filtering Protocol

Step 1: Initial Scan

  • Identify meeting phases (intro, main discussion, wrap-up)
  • Mark obvious side conversations and technical issues
  • Flag incomplete or unclear statements

Step 2: Relevance Assessment

  • Evaluate each segment for strategic value
  • Determine if content relates to meeting objectives
  • Assess completeness and accuracy of information

Step 3: Accuracy Verification

  • Cross-check contradictory statements
  • Flag information that seems incorrect
  • Note areas requiring clarification

Step 4: Context Preservation

  • Ensure decisions have sufficient context
  • Maintain background for action items
  • Preserve strategic discussion flow

Quality Assurance

Verification Standards

  • All decisions must have clear context and rationale
  • Action items must have specific owners and deadlines
  • Strategic themes must be supported by substantial discussion
  • Team dynamics assessment must be based on observable patterns

Uncertainty Handling

  • Flag potentially incorrect information for user confirmation
  • State confidence levels for interpretations
  • Request clarification for ambiguous content
  • Explicitly note when information is incomplete

Integration with Daily Brief

Meeting notes processed by this command feed directly into the daily brief:

  • Phase 2, Agent 3 (meeting-reviewer) scans for recent meeting files
  • Phase 3 cross-references action items against GitHub PRs and Linear issues
  • Section 13 (Meeting Follow-Up Tracker) tracks commitment completion

This creates accountability: decisions and action items from meetings are automatically tracked against actual execution in code and project management tools.

Learning Integration

  • Track meeting effectiveness patterns over time
  • Identify successful decision-making processes
  • Learn team communication preferences
  • Adapt filtering based on user feedback on relevance

Frequently asked questions

What does the Meeting Transcript AI skill do?

Process meeting recordings and notes into structured decisions, action items, and team dynamics with intelligent noise filtering

Why use Meeting Transcript on TypingMind?

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

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

Which AI models can use Meeting Transcript?

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 Transcript?

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

Is the Meeting Transcript AI skill free?

Yes. It is published on GitHub by huytieu 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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