chameleon-explain

Analyze Chameleon plugin enforcement rules and edit histories.

9|3|Updated May 10, 2026
One-click install
npx skills add https://github.com/crisnahine/chameleon --skill chameleon-explain
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: chameleon-explain
Source: https://github.com/crisnahine/chameleon/tree/main/plugin/skills/chameleon-explain
Command: npx skills add https://github.com/crisnahine/chameleon --skill chameleon-explain

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides in-depth analysis of enforcement rules and edit histories within the Chameleon plugin, helping users understand the behavior of the plugin and diagnose issues.

Core Features & Use Cases

  • Rule Analysis: Explain individual enforcement rules, including their calibration and override rates.
  • Edit History: Replay the last known state of a file and classify why the gate stayed silent.
  • Use Case: When a code review catches a defect that should have been blocked by Chameleon, use this Skill to understand why the rule was not triggered and how to improve it.

Quick Start

Use the /chameleon-explain <rule> command to analyze an enforcement rule. For example, /chameleon-explain import-preference-violation.

Frequently Asked Questions about chameleon-explain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why did my code review enforcement rule not block a defect during post-incident analysis?

Post-incident analysis uses edit history replay to classify why an enforcement rule stayed silent, checking if the rule was demoted, had a low would-block frequency, or was bypassed by an inline override.

How do I analyze Chameleon plugin enforcement rules and edit histories?

Analyze enforcement rules and edit histories by running a command like /chameleon-explain <rule> to identify why specific rules are active or demoted, and to review their would-block frequency and override rates.

What is rule demotion and how does inline override rate affect code review enforcement?

Rule demotion reduces enforcement strictness, while inline override rate measures how often rules are manually bypassed; both metrics help diagnose why a gate stayed silent during code review.

How do I optimize enforcement rules after a code review catches a missed defect?

Optimize enforcement rules by analyzing their calibration and edit histories to understand why the gate stayed silent, then adjusting rule configurations to improve future would-block frequency.

Can I replay the last known state of a file to see why a code review gate stayed silent?

Yes, edit history analysis replays the last known state of a file to classify why the gate stayed silent, helping you understand rule behavior and identify demoted rules or inline overrides.

Does the Chameleon plugin explain tool work for post-incident rule optimization without dependencies?

Yes, the analysis operates independently without dependencies, using scripts to analyze enforcement rules and edit histories for post-incident analysis and rule optimization in code review workflows.