Fireflies Team Meeting Intelligence

Task

Analyze team meeting patterns using Fireflies data — total hours in meetings, per-person participation, meeting frequency trends, average duration, and topic distribution.

Input

The user will provide a team name, time range, or specific people to analyze.

Example: "How much time did the engineering team spend in meetings last week?" or "Show me meeting trends for the last month"

Context

Strategy

1. Use @Fireflies/List UsersName it "Fireflies/List Users" and call it with @Fireflies/List Users to get the team roster and user details
2. Use @Fireflies/Get UserName it "Fireflies/Get User" and call it with @Fireflies/Get User to pull additional context for specific team members
3. Use @Fireflies/List TranscriptsName it "Fireflies/List Transcripts" and call it with @Fireflies/List Transcripts to pull all meetings in the time range
4. Use @Fireflies/Get TranscriptName it "Fireflies/Get Transcript" and call it with @Fireflies/Get Transcript for each meeting to extract duration, participants, and topics
5. Calculate aggregate metrics and identify patterns

Analysis Dimensions

• Meeting Time Analysis: Total hours spent in meetings per person and for the team
• Participant Frequency: Who attends the most meetings, who is in the fewest
• Meeting Duration Trends: Average meeting length, longest/shortest meetings, trend over time
• Topic Distribution: What topics come up most frequently across meetings
• Meeting Overlap: How often team members are double-booked or in back-to-back meetings
• Meeting Size: Average number of participants, meetings with too many or too few people

Output Structure

• Team Overview: Total meetings, total hours, average per person
• Per-Person Breakdown: Meeting count, total time, percentage of work week in meetings
• Duration Analysis: Average, median, min, max meeting lengths
• Frequency Trends: Meetings per day/week, trend direction
• Topic Heatmap: Most common discussion topics
• Recommendations: Suggestions for optimizing meeting time

Quality Guidelines

• Present data in tables or structured formats for easy scanning
• Compare against benchmarks (e.g., 30% of work week in meetings is typical)
• Flag outliers (someone in 30+ hours of meetings, or a 3-hour meeting)
• Include week-over-week or month-over-month trends when data is available

Output

A meeting intelligence report containing:

• Team and per-person meeting time metrics
• Duration and frequency trend analysis
• Topic distribution across meetings
• Actionable recommendations for meeting optimization