Meeting to Issues

Transform meeting transcripts into structured GitHub issues with intelligent action item extraction.

When to Use

• After team meetings, planning sessions, or retrospectives
• Converting recorded decisions into trackable work
• Extracting action items from standup notes or async discussions
• Creating issues from Zoom/Teams/Slack transcripts

Workflow

Step 1: Share the Transcript

Provide the meeting transcript in any format:

• Copy-paste from Zoom/Teams/Google Meet
• Upload a text file
• Share meeting notes from Notion/Confluence
• Paste Slack thread content

Step 2: Extract & Review Issues

The agent will:

1. Parse the transcript for action items, decisions, and tasks

2. Generate proposed GitHub issues with:

   • Clear, actionable titles
   • Detailed descriptions with context
   • Suggested labels (bug, enhancement, task, etc.)
   • Priority indicators
   • Assignee suggestions (if mentioned)
   • Links to related issues (if discussed)

3. Present issues for your review in a readable format

Step 3: Confirm & Create

Review the proposed issues and either:

• Approve all - Create all issues as-is
• Edit specific issues - Modify titles, descriptions, or labels
• Remove issues - Exclude items that shouldn't be tracked
• Add issues - Include anything the agent missed

Once confirmed, the agent creates all issues in your specified repository.

Analysis Criteria

The agent evaluates transcript content to identify:

Actionable Items

• Explicit assignments: "John will fix the auth bug"
• Todo items: "We need to update the docs"
• Decisions requiring implementation: "Let's add dark mode support"
• Bugs reported: "Users are seeing timeout errors"
• Feature requests: "Can we add export to CSV?"

Context Extraction

• Who: People mentioned in connection with tasks
• What: Technical details, requirements, acceptance criteria
• Why: Business justification, user impact
• When: Deadlines or urgency indicators
• Where: Components, files, or systems mentioned

Intelligent Labeling

• bug - Error reports, crashes, broken functionality
• enhancement - New features, improvements
• documentation - Docs updates, README changes
• task - General work items, refactoring
• question - Clarifications needed, open discussions
• urgent - Time-sensitive items
• blocked - Dependencies mentioned

Example Usage

Input transcript:

[10:00] Sarah: The login page is throwing 500 errors for Gmail users.
[10:01] Mike: I can look into that today. Probably an OAuth scope issue.
[10:02] Sarah: Thanks. Also, we should add the export feature users have been requesting.
[10:03] Mike: Good idea. Maybe that's a separate story though.
[10:04] Sarah: Agreed. Let's also update the API docs - they're outdated.
[10:05] Mike: I'll handle the login bug. Can you or Alex take the docs?

Proposed issues:

1. Fix 500 errors on login for Gmail users

   • Description: Users authenticating with Gmail are encountering 500 errors on the login page. Initial investigation suggests this may be an OAuth scope configuration issue.
   • Labels: bug, urgent
   • Suggested assignee: Mike
   • Priority: High

2. Add data export feature

   • Description: Users have requested the ability to export their data. Discussed in standup - should be tracked as a separate feature request.
   • Labels: enhancement
   • Priority: Medium

3. Update API documentation

   • Description: The API documentation is currently outdated and needs to be refreshed to reflect the current state of the API.
   • Labels: documentation
   • Suggested assignee: Sarah or Alex
   • Priority: Medium

Step 4: Create Issues

After confirmation:

Creating issues in owner/repo...
✓ #123 Fix 500 errors on login for Gmail users
✓ #124 Add data export feature  
✓ #125 Update API documentation

Created 3 issues successfully.

Data Format

Issues are structured as JSON before creation:

{
  "issues": [
    {
      "title": "Fix 500 errors on login for Gmail users",
      "body": "Users authenticating with Gmail are encountering 500 errors...",
      "labels": ["bug", "urgent"],
      "assignee": "mike",
      "priority": "high",
      "reasoning": "Explicit bug report with technical details and assignee mentioned"
    }
  ]
}

Best Practices

For Better Results

• Include full context in transcripts (who said what)
• Mention specific components, files, or systems
• Note any explicit assignments or deadlines
• Include technical details (error messages, versions, etc.)

Review Checklist

• ✓ Titles are clear and actionable
• ✓ Descriptions have enough context for someone not in the meeting
• ✓ Labels accurately categorize the work
• ✓ No duplicate issues with existing backlog
• ✓ Priorities reflect actual urgency
• ✓ Assignees are correct (or left unassigned)

Safety Features

• No automatic creation - Issues only created after explicit approval
• Review phase - All issues presented for editing before submission
• Dry-run option - Preview what would be created without committing
• Rollback support - Issues created in batch can be closed if needed
• Audit trail - All created issues link back to the meeting/transcript

Configuration

The skill can be customized per repository:

# Create in a specific repo
Repository: owner/repo

# Apply custom label mappings
Label mapping: bug → incident, enhancement → feature-request

# Default assignees
Default assignee: None (leave unassigned)

# Auto-apply labels
Additional labels: from-meeting, needs-refinement

Files

meeting-to-issues/
├── SKILL.md              # This file
├── scripts/
│   ├── parse.sh          # Extract action items from transcript
│   ├── create-issues.sh  # Batch create issues via gh CLI
│   └── preview.sh        # Show what would be created
├── transcript.txt        # User-provided transcript (git-ignored)
├── proposed-issues.json  # Extracted issues (git-ignored)
└── created-issues.json   # Created issue references (git-ignored)

Notes

• Requires gh CLI authenticated with write access
• Run gh auth status to verify permissions
• Supports Markdown formatting in issue bodies
• Can handle multiple meeting formats (timestamps optional)
• Works with partial transcripts or bullet-point notes
• Agent will ask clarifying questions if context is unclear

Limitations

• Cannot auto-assign to users not in the repository
• Labels must exist in target repository (creates standard ones if missing)
• Long transcripts may need to be split for optimal parsing
• Highly ambiguous discussions may require manual clarification