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mengran-aurorie / behavior-os

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BehaviorOS

89
18
100% credibility
Found Mar 29, 2026 at 89 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

BehaviorOS compiles detailed profiles of historical and fictional figures into shareable decision summaries or prompts that can be used with AI chat tools for consistent, persona-based advice.

How It Works

1
🔍 Discover wise advisors

You hear about BehaviorOS, a simple tool that lets famous thinkers like Steve Jobs or Sun Tzu give advice on your tough choices.

2
📦 Get it ready

With one easy command, you add it to your computer, like installing a helpful app.

3
đź‘Ą Pick your thinkers

Choose a few characters from the built-in collection, like a strategic general or a thoughtful leader.

4
đź’­ Ask your question

Type in a real-life dilemma, like 'Should I ship now or perfect it later?'

5
🧠 See their wisdom

Watch as each thinker gives a clear, punchy answer, or blend them for a new perspective that feels spot-on.

6
📱 Share or chat

Copy the advice to share with friends, or send it to your AI helper for deeper thoughts.

âś… Decide with confidence

You feel like you have a council of great minds helping you make smarter choices every time.

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Star Growth

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AI-Generated Review

What is behavior-os?

BehaviorOS is a Python CLI tool for compiling structured behaviors—like those of Sun Tzu or Steve Jobs—into deterministic prompts for AI agents. It fuses multiple personas without averaging them into vague mush, resolving conflicts slot-by-slot for consistent outputs, then injects into Claude or generates shareable decision summaries via `mindset run --share`. Developers get explainable, non-hallucinating responses to queries, modeling everything from ostrich aggressive behavior to osprey courtship behavior in agentic systems.

Why is it gaining traction?

Unlike basic prompt personas that collapse under blending, BehaviorOS delivers emergent decisions with full traces via `--explain`, plus a library of 51 benchmarked packs for instant fusion like Steve Jobs (ship fast) vs. Marcus Aurelius (integrity first). The `--share` mode hooks users with screenshot-ready multi-perspective outputs—no API keys needed—while `mindset compile` turns raw sources into packs, making behavioros a runtime layer over shaky LLM tendencies.

Who should use this?

AI engineers prototyping agentic mindsets for decision tools, prompt crafters blending historical figures for strategy sims (e.g., Cao Cao's pragmatism vs. Confucius harmony), or teams using oscillatory behavior models in simulations. Ideal for devs evaluating ostentatious behavior in marketing agents or ostapenko behavior in competitive scenarios.

Verdict

Worth pip-installing for agent experiments—89 stars and 1.0% credibility score signal early v0.3 maturity, but comprehensive docs, CLI polish, and passing tests lower the risk. Skip if you need production scale; otherwise, fuse a pack and query today.

(187 words)

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