SamadhiFire

毛选拆局.skill

38
10
69% credibility
Found Apr 09, 2026 at 38 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
HTML
AI Summary

A repository for an AI skill that guides users through structured problem-solving via clarification, categorization, scenarios, methods, risk checks, and formatted outputs.

How It Works

1
👀 Discover the thinking guide

You hear about a special AI helper inspired by classic problem-solving wisdom that breaks down tough challenges step by step.

2
📥 Bring it home

You easily download the guide and add it to your everyday AI chat companion with a few simple steps.

3
💬 Share your puzzle

You describe the real-life problem you're facing, like a tricky decision or complicated situation at work.

4
Get clarifying questions

The helper asks gentle, focused questions to fully understand the key parts of your issue without overwhelming you.

5
🔍 See the breakdown

It sorts your problem into clear categories, matches it to everyday scenarios, and picks the best strategies to try.

6
⚠️ Spot the watch-outs

It highlights any potential traps or risks so you can steer clear and stay on a safe path.

📄 Receive your roadmap

You get a neat summary or colorful web report with a clear plan to tackle your challenge confidently.

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Star Growth

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AI-Generated Review

What is maozedong-maoxuan-skill?

This HTML skill deploys a Maozedong Maoxuan-inspired framework for AI agents, breaking down complex problems via a fixed chain: clarify ambiguities, categorize issues, map scenarios, apply methods, flag risks, and route to self-contained HTML reports. Built for GitHub skill directories like those for Anthropic Claude, Copilot, or openclaw setups, it turns vague queries into structured analyses using YAML agent configs and a Python validator. Users get reliable, visualized outputs without drifting prompts.

Why is it gaining traction?

It stands out in the GitHub skill marketplace and awesome lists by enforcing minimal handoffs between layers—no bloated all-in-one prompts—yielding tighter reasoning than ad-hoc chains. The antigravity-style compose flexibility lets you slot it into multi-agent flows, while instant skill validation catches YAML frontmatter errors fast. Developers hook on the Maoxuan rigor for reproducible breakdowns in strategy or ops tasks.

Who should use this?

Prompt engineers tuning Claude or Copilot agents for decision workflows, AI devs in GitHub skill directories handling business case decompositions, and strategists applying Maoxuan tactics to puzzles or risk audits via HTML exports.

Verdict

At 38 stars and 0.7% credibility, it's immature with thin tests but excellent layered docs—fork it for custom AI skills if structured prompting clicks, otherwise stick to proven GitHub skill alternatives.

(178 words)

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