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hoangsonww / sprint-summary

Summarize a sprint's worth of Claude Code activity — sessions grouped by project (cwd), per-model cost breakdown, token efficiency (cache hit rate, compaction baselines), subagent effectiveness from workflow API, velocity metrics (turn_count, turn_duration_ms), and tool diversity across the sprint.

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SKILL.md
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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

  2. 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