growth-engine

Track task execution data and extract repeatable patterns into standard operating procedures.

1|Updated Apr 18, 2026
One-click install
npx skills add https://github.com/CC90210/CMO-Agent --skill growth-engine-cc90210
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: growth-engine
Source: https://github.com/CC90210/CMO-Agent/tree/main/skills/growth-engine
Command: npx skills add https://github.com/CC90210/CMO-Agent --skill growth-engine-cc90210

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires memory-management, sop-breakdown.

What problem does it solve?

This Skill solves the problem of stagnant AI performance by creating a closed-loop system that tracks task outcomes, identifies skill gaps, and systematically promotes successful patterns into standard operating procedures.

Core Features & Use Cases

  • Pattern Extraction: Automatically identifies repeatable successful workflows from daily task execution.
  • Skill Gap Analysis: Detects failures or missing capabilities and logs them for future research and acquisition.
  • Evolution Reporting: Generates weekly and monthly performance audits to track growth velocity and capability frontier expansion.

Quick Start

Trigger the growth engine to perform a monthly audit and generate an evolution report based on recent task performance.

Frequently Asked Questions about growth-engine

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

FAQPage Schema
How do I automate pattern extraction from task execution data to improve workflows?

Automated pattern extraction identifies repeatable successful workflows from daily task execution data and systematically promotes them into standard operating procedures to prevent stagnant performance.

How does a closed-loop learning system detect skill gaps in autonomous task cycles?

A closed-loop learning system detects skill gaps by tracking task outcomes across complex cycles, logging failures or missing capabilities for future research and acquisition to refine performance metrics.

Do I need memory management and SOP breakdown systems to track capability expansion?

Yes, you need memory management and SOP breakdown systems to maintain a high-confidence knowledge base that supports tracking task execution data and generating evolution reports.

What is the best way to audit performance and generate evolution reports for capability frontier expansion?

The best way to audit performance is triggering a monthly audit to generate an evolution report, which tracks growth velocity and capability frontier expansion from recent task performance data.

Can I use autonomous learning to refine performance metrics across complex task cycles?

Yes, autonomous learning systematizes capability expansion by operating across complex task cycles to identify skill gaps, refine performance metrics, and extract repeatable patterns into standard operating procedures.

Why does AI performance stagnate without standard operating procedures extracted from daily tasks?

AI performance stagnates without standard operating procedures because there is no closed-loop system to track task outcomes, identify skill gaps, and promote successful patterns into repeatable workflows.