peteromallet

peteromallet / desloppify

Public

Agent harness to make your slop code well-engineered and beautiful.

1,059
61
100% credibility
Found Feb 20, 2026 at 219 stars 5x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Desloppify scans codebases for quality issues like duplication and complexity, tracks fixes with scores, and guides AI agents to improve them across multiple languages.

How It Works

1
🔍 Spot the badge

You notice a cool health badge on a project's page and learn about a helpful code checker.

2
📥 Get the helper

You grab the free tool with a simple download so it can watch your code.

3
🩺 Check your code health

Run a quick check and see your first score showing what's great and what needs love.

4
📊 See the dashboard

View easy charts of progress by easy fixes, big refactors, and style tweaks.

5
Pick your fix
⚡
Auto-fix

Let it clean up simple stuff like extra logs automatically.

🛠️
Manual fix

Follow tips to improve tricky parts yourself.

6
✅ Mark it done

Tell the tool you fixed it or decided to skip, with a quick note.

🎉 Healthy codebase

Your score climbs, issues vanish, and you add a shiny badge to show off your tidy project.

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Star Growth

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AI-Generated Review

What is desloppify?

Desloppify is a Python CLI agent harness that scans codebases for dead code, duplication, complexity, and subjective smells across TypeScript, Python, C#/.NET, Dart, and GDScript. It tracks issues persistently, computes objective and strict health scores (penalizing open or wontfix debt), and generates README badges plus copy-paste prompts for AI agents like GitHub Copilot or Claude to fix them iteratively. Run `desloppify scan`, `status`, `next`, and `resolve` to turn agent-generated slop into engineered code.

Why is it gaining traction?

It bridges vibe coding speed with engineering rigor via an agent harness AI workflow—`desloppify next` queues one high-impact fix for your agent github copilot reddit thread or Claude session, while auto-fixing mechanical issues like unused imports. Unlike generic linters, the strict score and subjective review prep (via `review --prepare`) harness anthropic or OpenAI agents for tasteful refactors, with badges signaling progress on GitHub repos. Agent github action integration and Discord vibe engineering community fuel shares.

Who should use this?

Solo devs or small teams wielding agent github copilot intellij, Cursor, or Claude for fast prototypes, but battling tech debt in mid-sized GitHub repos. Perfect for full-stack builders at Shopify-scale wanting langchain-like agent harnessing without QA teams, or Python/TS maintainers chasing 95+ strict scores via `fix` and `issues` commands.

Verdict

Worth a `pip install` for agent-heavy workflows—221 stars and agent harness claude code prompts deliver quick wins despite 1.0% credibility signaling early-stage maturity. Docs shine, but test new languages yourself; it's a solid harness for google github agent experiments today.

(198 words)

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