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.
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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
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Handle ActiveCampaign contact and marketing tasks through Rube MCP, a connection for agent tools. Find or create contacts, manage tags and subscriptions, enroll contacts in existing automated workflows, and create follow-up tasks.
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Research competitors’ live Meta and Google ads to identify opening hooks, offers, calls to action, and landing pages. Receive a sourced creative brief and up to three test ideas adapted to your product.
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Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
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Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
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Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
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Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.
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