Sprint Summary

Generate a sprint summary from Claude Code Agent Monitor data.

Input

The user provides: $ARGUMENTS

This may be:

• A sprint duration: "last 2 weeks", "last 10 days"
• A date range: "2025-03-31 to 2025-04-13"
• "current sprint" (default: last 14 days)

Procedure

1. Fetch sprint data from http://localhost:4820:

• GET /api/sessions?limit=500 — all sessions in range (default sort: most recently updated first)
• GET /api/analytics — aggregated metrics
• GET /api/pricing/cost — total costs
• For high-value sessions: GET /api/events?session_id={id} — event details

1. Compile sprint summary:

### 🎯 Sprint Overview

• Sprint period: start] to end]
• Total sessions: N (completed: N, errored: N, abandoned: N)
• Total development hours with Claude Code: N
• Total cost: $X.XX
• Overall completion rate: N%

### 📦 Deliverables Group sessions by working directory (project):

• Project A (/path/to/project)
• N sessions, N hours, key activities
• Project B (/path/to/other)
• N sessions, N hours, key activities

### 📊 Velocity Metrics | Metric | Sprint | Previous Sprint | Trend | |--------|--------|-----------------|-------| | Sessions/day | N | N | ↑/↓ | | Avg session duration | Nm | Nm | ↑/↓ | | Cost/session | $N | $N | ↑/↓ | | Tokens/session | N | N | ↑/↓ | | Completion rate | N% | N% | ↑/↓ |

### 🛠 Technology Breakdown

• Models used with distribution percentages
• Top 15 tools by usage with category grouping
• Subagent utilization rate

### ⚡ Efficiency Analysis

• Token efficiency: cache hit rate, compaction frequency
• Cost per completed task
• Time-to-first-output (avg across sessions)
• Error recovery rate (sessions that recovered from errors)

### 🔄 Retrospective Data Points

• What went well: Highest-efficiency sessions, best completion rates
• What could improve: Most expensive sessions, highest error rates
• Action items: Data-driven suggestions for next sprint

Output Format

Professional sprint report suitable for sharing with team leads or managers:

• Executive summary paragraph (5 sentences max)
• Structured data tables with trend indicators
• Grouped deliverables by project
• Numbered action items at the end