Generate coaching notes for a manager preparing a 1:1 with a rep, covering activity, engagement quality, conversion efficiency, and areas for improvement.
name rep-coaching-brief description Generate coaching notes for a manager preparing a 1:1 with a rep, covering activity, engagement quality, conversion efficiency, and areas for improvement. metadata {"author":"amplemarket","version":"1.0.4","category":"Team & Coaching"} compatibility Requires Amplemarket MCP server Rep Coaching Brief Generate coaching notes for a manager preparing a 1:1 with a rep, covering activity, engagement quality, conversion efficiency, and areas for improvement. Instructions When a manager wants coaching notes on a specific rep, query analytics for that rep's performance across key metrics, compare to team averages, and present a structured brief for the 1:1. Steps Identify the rep and scope. The user will name a rep or provide their email. Default to last 30 days. Ask if they want a different timeframe. Gather the data by submitting these analytics questions via mcp__claude_ai_Amplemarket__ask_analytics : Rep's outreach volume across all channels (email, LinkedIn, calls) Rep's reply rate, open rate, interested rate Rep's meetings booked Rep's bounce rate Rep's Duo leads actioned and dismiss rate (if Duo is enabled) Rep's top sequences by reply rate Rep's worst sequences by reply rate Team averages for the same metrics (for comparison) Submit all in parallel, poll with mcp__claude_ai_Amplemarket__get_analytics_result . Analyze relative to the team. For each metric, compare the rep to the team average. Identify: Where they're above average (strengths to reinforce) Where they're below average (areas for coaching) Any notable patterns (e.g., high volume but low reply rate = messaging issue, low volume but high reply rate = capacity opportunity) Present a well-formatted coaching brief. Lead with a quick summary of the rep's standing, then break down strengths, areas for improvement, and specific talking points for the 1:1. Include the data backing each point. Examples User prompt: "Give me coaching notes for David Kim ahead of our 1:1" Simple example output: The agent finds David's email volume is 15% below team average, but his reply rate is 2x the average. Meetings booked are average. His top sequence outperforms the team's best. Recommends the coaching focus on increasing David's volume since his engagement quality is excellent -- more sends at his reply rate would likely mean more meetings. Presented as a brief with a strengths section, improvement areas section, and suggested 1:1 talking points. Troubleshooting Problem Solution Rep name is ambiguous Ask for the rep's email to match exactly in analytics queries.