eterdis-protoloop

Name: eterdis-protoloop
Availability: InStock
Author: eterdis

Design and manage Track Two innovation experiments with YAML frontmatter and monthly heartbeat reviews.

6|Updated Apr 1, 2026

Search Tags:#strategy #innovation #workflows #experimentation #intake #protoloop

Ready to run

npx skills add https://github.com/eterdis/strategy-skills --skill eterdis-protoloop

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: eterdis-protoloop
Source: https://github.com/eterdis/strategy-skills/tree/main/protoloop-setup
Command: npx skills add https://github.com/eterdis/strategy-skills --skill eterdis-protoloop

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Protoloop provides a protected, systematic approach to designing and running Track Two experimentation within an organization, turning loosely-structured ideas into repeatable learning loops.

Core Features & Use Cases

Diagnostic mode to design the full protoloop, intake channels, team, and exit paths.
Monthly heartbeat for ongoing review, learning, and momentum management.
Forward-loading and portfolio view to maintain a learning trajectory across loops and avoid dead-end experiments.
Exit paths framework to graduate, spin out, archive, or kill loops based on evidence.

Quick Start

Run a Diagnostic Protoloop from scratch to design intake, loops, team, and exit paths for a new initiative.

Frequently Asked Questions about eterdis-protoloop

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

FAQPage Schema

What is a Track Two innovation protoloop and when do I need one?▼

A Track Two innovation protoloop is a protected, systematic approach to designing and running iterative experimentation within an organization. You need one to transform loosely-structured ideas into repeatable learning loops.

How do I design intake channels and exit paths for innovation experiments?▼

You can design intake channels and exit paths for innovation experiments by running a Diagnostic mode that maps out the full protoloop, team structure, and graduation, spin out, archive, or kill pathways based on evidence.

What is the best way to manage ongoing momentum for iterative prototyping?▼

The best way to manage ongoing momentum for iterative prototyping is to establish a monthly heartbeat for regular review and learning, combined with a forward-loading portfolio view to maintain a learning trajectory and avoid dead-end experiments.

Can I use YAML frontmatter and company-context.md to govern experimentation workflows?▼

Yes, you can use YAML frontmatter with name and description definitions alongside company-context.md to govern experimentation workflows, define modes, and provide update guidance for your Track Two innovation engine.

Does this prototyping framework support diverse frontline initiatives at scale?▼

Yes, the framework supports diverse frontline initiatives at scale by applying governance to iterative experiments, intake design, monthly heartbeats, and exit pathways across a portfolio view of multiple protected learning loops.