Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill transforms technical git commits into polished, user-friendly changelogs that your customers and users will actually understand and appreciate.
From your project repository:
Create a changelog from commits since last release
Generate changelog for all commits from the past week
Create release notes for version 2.5.0
Create a changelog for all commits between March 1 and March 15
Create a changelog for commits since v2.4.0, using my changelog
guidelines from CHANGELOG_STYLE.md
User: "Create a changelog for commits from the past 7 days"
Output:
# Updates - Week of March 10, 2024
## ✨ New Features
- **Team Workspaces**: Create separate workspaces for different
projects. Invite team members and keep everything organized.
- **Keyboard Shortcuts**: Press ? to see all available shortcuts.
Navigate faster without touching your mouse.
## 🔧 Improvements
- **Faster Sync**: Files now sync 2x faster across devices
- **Better Search**: Search now includes file contents, not just titles
## 🐛 Fixes
- Fixed issue where large images wouldn't upload
- Resolved timezone confusion in scheduled posts
- Corrected notification badge count
Inspired by: Manik Aggarwal's use case from Lenny's Newsletter
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
日本語の概要は準備中です。原文の説明を表示しています。
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。