Skip to content
cccskills
FreePublished on GitHub

meeting-intelligence

Analyze meeting transcripts to extract decisions, action items, blockers, sentiment, and generate follow-up emails. Use when user provides meeting notes, transcripts, or recordings and needs structured summaries or action tracking.

The English summary is being prepared. Showing the original description.

Run score Not tested

See how to install

Files included (1)

  • SKILL.md4.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Meeting Intelligence System

Transform meeting transcripts into actionable insights, decisions, and follow-ups.

When to Use This Skill

Activate when the user:

  • Provides a meeting transcript or recording
  • Asks to "analyze this meeting"
  • Needs action items extracted from notes
  • Wants to generate meeting minutes
  • Asks for decisions made in a meeting
  • Needs a follow-up email created
  • Mentions meeting notes or transcripts

Instructions

  1. Extract Meeting Metadata

    • Identify meeting title/topic
    • Note participants (if mentioned)
    • Determine meeting date/time (if available)
    • Identify meeting type (standup, planning, retrospective, etc.)
  2. Identify Decisions Made

    • Extract all explicit decisions
    • Note who made each decision (if clear)
    • Include rationale for decisions (if stated)
    • Flag tentative decisions vs. final decisions
    • Note decisions that need follow-up approval
  3. Extract Action Items

    • List all tasks assigned or volunteered
    • Identify owner for each action item
    • Note deadlines or timeframes mentioned
    • Flag action items without clear owners
    • Prioritize action items (if priority discussed)
    • Note dependencies between action items
  4. Identify Blockers and Risks

    • Extract mentioned blockers
    • Note risks or concerns raised
    • Identify unresolved issues
    • Flag items needing escalation
    • Note resource constraints mentioned
  5. Analyze Discussion Sentiment

    • Gauge overall meeting tone (productive, tense, confused, aligned)
    • Identify areas of agreement and disagreement
    • Note team morale indicators
    • Flag conflict or tension points
  6. Extract Key Topics Discussed

    • Summarize main discussion points
    • Note questions raised
    • Identify topics needing follow-up
    • Highlight important context or background
  7. Generate Follow-Up Communications

    • Create meeting minutes/summary
    • Draft action item tracking email
    • Suggest calendar invites for follow-ups
    • Recommend next steps

Output Format

# Meeting Summary: [Title]
**Date**: [Date] | **Participants**: [Names]

## Executive Summary
[2-3 sentence overview of meeting purpose and outcome]

## Decisions Made
1. **[Decision]**
   - Owner: [Name]
   - Rationale: [Why]
   - Status: Final / Needs approval

## Action Items
| Priority | Action | Owner | Deadline | Status |
|----------|--------|-------|----------|--------|
| High | [Task] | [Name] | [Date] | Not started |
| Medium | [Task] | [Name] | [Date] | Not started |

## Blockers & Risks
1. **[Blocker]** - [Impact] - Needs: [Action]
2. **[Risk]** - [Mitigation plan]

## Key Discussion Points
- [Topic 1]: [Summary]
- [Topic 2]: [Summary]

## Open Questions
1. [Question] - Owner: [Who will answer]

## Sentiment Analysis
- **Overall Tone**: [productive/tense/etc.]
- **Team Alignment**: [high/medium/low]
- **Concerns Raised**: [Summary]

## Follow-Up Email Draft

Subject: Action Items from [Meeting Title] - [Date]

Hi team,

Thanks for joining today's [meeting type]. Here are our key outcomes:

**Decisions:**
- [Decision 1]

**Your Action Items:**
[Name]: [Task] by [Date]

**Blockers:**
- [Blocker] - please [action]

Next meeting: [Date/Time]

Best,
[Your name]

Examples

User: "Analyze this standup transcript" Response: Extract blockers mentioned → List action items per person → Flag impediments → Note team velocity concerns → Generate summary with focus on blockers

User: "Create action items from this product planning meeting" Response: Identify all decisions (feature prioritization) → Extract action items (design mockups, tech spec) → Assign owners → Set deadlines → Create tracking table → Draft follow-up email

Best Practices

  • Be specific with action items (not vague "look into X")
  • Always try to identify owners (flag if unclear)
  • Differentiate between decisions and proposals
  • Preserve important context for decisions
  • Flag action items without deadlines
  • Note commitments made by each participant
  • Include relevant quotes for controversial decisions
  • Use clear, scannable formatting
  • Prioritize action items by urgency
  • Flag dependencies between tasks
  • Generate professional, actionable follow-up emails

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

The English summary is being prepared. Showing the original description.

OneWave-AI/claude-skills368Updated Oct 20, 2026

See all skills by OneWave-AI

Report a problem with this skill