nnennandukwe

This repo is a public, docs-first reference for teams that want agentic coding without chaos. It focuses on the patterns that protect code integrity while still preserving speed: plan, permission, verification, and tool trust.

13
5
100% credibility
Found Apr 03, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

A documentation-first resource offering patterns, scorecards, diagrams, and examples for safely governing AI agents in coding workflows.

How It Works

1
🔍 Discover the Guide

You hear about this helpful collection of ideas for keeping AI coding assistants safe and effective.

2
📖 Explore the Overview

You read simple explanations of five key checks that protect your code while letting AI work quickly.

3
📊 Check Your Setup

You grab the scorecard to rate how well your current AI tools guard against mistakes and risks.

4
Pick Your Role
👔
Team Leader

Use diagrams and scorecards to guide your team's standards and expectations.

🔧
Platform Builder

Study the check details and ready-to-use examples for your own tools.

💻
Daily User

Follow the checklists to make your personal workflow safer right away.

5
Try the Examples

You copy simple templates and visuals to test in your projects or share with your team.

🎉 Confident AI Use

Now your coding with AI feels secure, fast, and reliable, helping everyone work better.

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Star Growth

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AI-Generated Review

What is governed-agent-autonomy-patterns?

This public repo delivers docs-first patterns for safe agentic coding, tackling the chaos of AI agents that write and execute code too fast without checks. It outlines five gates—plan, permission, tool trust, verification, and runtime accountability—to enforce code integrity while keeping velocity high. Developers get scorecards, diagrams, templates, and checklists to evaluate tools or build governed workflows, all in a lightweight, repurposable format.

Why is it gaining traction?

Unlike speed-obsessed agent frameworks, it prioritizes a control plane that makes boundaries accelerate adoption, with visuals and examples pulled straight from production. The hook is its versatility: snag diagrams for talks, scorecards for vendor reviews, or templates for GitHub Actions and API integrations in agentic pipelines. Early adopters value the public repo's focus on runtime visibility, like quota tracking and spend attribution, over raw generation power.

Who should use this?

Engineering leaders auditing agentic tools for team rollouts. Platform teams designing governed publish pipelines or runtime accountability for remote agents. Staff engineers demanding checklists for permission gates and tool trust in public lobbies or private repo workflows.

Verdict

Grab it if you're serious about agentic coding without disasters—strong docs and practical templates outweigh the 1.0% credibility score and 13 stars signaling early maturity. Fork and adapt now; it'll mature as AI agents hit prime time.

(178 words)

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