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Humanize

Current Version: 1.14.0

Derived from the GAAC (GitHub-as-a-Context) project.

A Claude Code plugin that provides iterative development with independent AI review. Build with confidence through continuous feedback loops.

What is RLCR?

RLCR stands for Ralph-Loop with Codex Review, inspired by the official ralph-loop plugin and enhanced with independent Codex review. The name also reads as Reinforcement Learning with Code Review -- reflecting the iterative cycle where AI-generated code is continuously refined through external review feedback.

Core Concepts

  • Iteration over Perfection -- Instead of expecting perfect output in one shot, Humanize leverages continuous feedback loops where issues are caught early and refined incrementally.
  • One Build + One Review -- Claude implements, Codex independently reviews. No blind spots.
  • Ralph Loop with Swarm Mode -- Iterative refinement continues until all acceptance criteria are met. Optionally parallelize with Agent Teams.

How It Works

RLCR Workflow

The loop has two phases: Implementation (Claude works, Codex reviews summaries) and Code Review (Codex checks code quality with severity markers). Issues feed back into implementation until resolved.

Install

# Add humania marketplace
/plugin marketplace add humania-org/humanize
# If you want to use development branch for experimental features
/plugin marketplace add humania-org/humanize#dev
# Then install humanize plugin
/plugin install humanize@humania

Requires codex CLI for review. See the full Installation Guide for prerequisites and alternative setup options.

Quick Start

  1. Generate a plan from your draft:

    /humanize:gen-plan --input draft.md --output docs/plan.md
  2. Run the loop:

    /humanize:start-rlcr-loop docs/plan.md
  3. Monitor progress:

    source <path/to/humanize>/scripts/humanize.sh
    humanize monitor rlcr

Monitor Dashboard

Humanize Monitor

Documentation

License

MIT