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Sprint Summary

CommunityPopular
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.

Overview

Publisherhoangsonww
RepositoryClaude-Code-Agent-Monitor
Skill namesprint-summary
Stars
1.1K
Forks
260
Bundled files
1
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hoangsonww on GitHub. Read the source before you install it.

Installation

Install the Sprint Summary AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-productivity/skills/sprint-summary
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git /tmp/Claude-Code-Agent-Monitor
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Agent-Monitor/plugins/ccam-productivity/skills/sprint-summary .claude/skills/sprint-summary
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sprint Summary in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sprint Summary on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sprint Summary is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

    MetricSprintPrevious SprintTrend
    Sessions/dayNN↑/↓
    Avg session durationNmNm↑/↓
    Cost/session$N$N↑/↓
    Tokens/sessionNN↑/↓
    Completion rateN%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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sprint Summary AI skill do?

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.

Why use Sprint Summary on TypingMind?

Because you install it once and use it with any model. Sprint Summary is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sprint Summary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-productivity/skills/sprint-summary. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sprint Summary?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sprint Summary?

As many as you like. As long as a model supports skills, you can use Sprint Summary with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sprint Summary AI skill free?

Yes. It is published on GitHub by hoangsonww under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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