johnpcutler

johnpcutler / tbm-recommender

Public

A skill that efficiently recommends posts from The Beautiful Mess

18
1
100% credibility
Found Apr 28, 2026 at 18 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
AI Summary

A collection of about 440 posts from John Cutler's 'The Beautiful Mess' newsletter, formatted as a skill for AI coding agents to search and recommend relevant content on product management topics.

How It Works

1
📰 Discover TBM Newsletter

You hear about John Cutler's insightful posts on product management and want quick access to them through your AI helper.

2
🔍 Find the Recommender Skill

You come across this handy skill that lets your AI buddy search and suggest the best matching posts from hundreds of articles.

3
✨ Add to Your AI Helper

You simply save the skill into your AI companion's special learning spot, and it starts working right away.

4
💭 Ask About a Topic

You chat with your AI about things like strategy, prioritization, or team leadership, mentioning TBM or related ideas.

5
🎯 Get Smart Suggestions

Your AI quickly finds and shares the most relevant posts with links, saving you time and effort.

📖 Dive into Wisdom

You explore the recommended articles, gaining fresh insights that make your work better and more effective.

Sign up to see the full architecture

4 more

Sign Up Free

Star Growth

See how this repo grew from 18 to 18 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is tbm-recommender?

TBM Recommender is a lightweight GitHub skill that efficiently recommends posts from John Cutler's The Beautiful Mess newsletter, indexing around 440 entries on product management, strategy, and systems thinking. Packaged in the open SKILL.md format, it plugs into AI coding agents like Cursor, Claude, or Copilot, automatically surfacing relevant links when you query related topics. Developers get instant access to curated wisdom without leaving their agent workflow.

Why is it gaining traction?

In the GitHub skill directory and marketplace, it stands out with a three-tier retrieval system that keeps token costs low—typically 3,000-15,000 input tokens per query—making it practical for skill GitHub agents from Anthropic's Claude to OpenClaw setups. The auto-activation on mentions of TBM or Cutler hooks users immediately, while the content graph lets agents explore related posts on demand. It's a smart addition to any GitHub skill set for PM-focused chats.

Who should use this?

Product managers using AI agents for brainstorming roadmaps, prioritization, or org design will find it indispensable during strategy sessions. Engineering leads querying Claude or Copilot about metrics, delivery, or leadership get targeted TBM posts without manual searching. Teams experimenting with skill GitHub integrations for continuous improvement workflows benefit most.

Verdict

Worth cloning into your agent's skills folder if you're deep into PM topics—solid docs and low token overhead make it immediately useful despite 18 stars and a 1.0% credibility score signaling early maturity. Test it for your workflow; it's MIT-licensed and expands easily as the GitHub skill ecosystem grows.

(178 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.