byte721

byte721 / counsel

Public

An AI defense attorney for high-profile public disputes. Pick a side. Counsel builds the defense.

36
3
100% credibility
Found Apr 29, 2026 at 36 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Counsel is an open-source Python tool that generates structured AI-powered defense briefs for public disputes using user-provided cases with allegations and evidence.

How It Works

1
🔍 Discover Counsel

You find this fun AI tool online that acts like a smart defense lawyer for big public arguments and debates.

2
đź’» Set it up

Download the tool to your computer and get it ready to use in just a few minutes.

3
đź”— Connect AI helper

Link the tool to a powerful AI service so it can think deeply and craft arguments.

4
đź“‹ Build your case

Pick who to defend, list the accusations against them, and add helpful facts or proofs in a simple description file.

5
⚖️ Ask for defense

Tell the tool to create a full defense strategy based on your case.

đź“„ Get your brief

Enjoy a complete, professional-looking defense document you can read, save, or share right away.

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Star Growth

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AI-Generated Review

What is counsel?

Counsel is a Python CLI tool that acts as an AI defense attorney for public disputes on ai counsel github. Feed it a JSON case file detailing a client, allegations, and supporting evidence, and it uses OpenAI or xAI models like GPT-4o or Grok to generate a structured defense brief—including a core theory, factual summary, per-allegation responses, and closing argument. It's built for quickly drafting arguments in high-profile spats, like defending execs in media firestorms, without pretending to judge guilt.

Why is it gaining traction?

It stands out by enforcing six defense theory archetypes—denial, reframing, justification, procedural, affirmative, mitigation—for consistent, lawyerly output, saved as both JSON and readable text. Devs love the dead-simple CLI (counsel represent --case file.json --print) and provider switching (--provider xai), making it a lightweight way to test LLM reasoning in adversarial scenarios versus generic chat wrappers. The hook: example cases for real-world drama, like Musk vs. critics, spark quick experiments.

Who should use this?

AI researchers prototyping legal or argumentative agents, journalists needing rapid counter-narratives for counseling deutsch-style public defenses, or devs building bots that track defense attorneys monitoring Trump prosecutions. Ideal for counselor deutsch experiments in LLM bias or defense attorney vs prosecutor simulations, not actual litigation.

Verdict

Try it for LLM research or fun briefs—solid docs, pytest suite, MIT license—but with 36 stars and 1.0% credibility score, it's early beta research ware, not production-ready. Pair with your own cases for best results.

(178 words)

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