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A structured execution protocol for echoes in AI systems. It includes a series of echoes designed to optimize, evaluate, and plan processes in conversational AI

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🧠 Echo Protocol Repository

Introduction

Welcome to the Echo Protocol repository. This collection contains structured echoes designed to guide AI processes in areas like evaluation, diagnosis, reflection, simulation, planning, and more.

Each echo defines a clear cognitive flow and can be executed by assistants, agents, or AI systems that support structured reasoning.

There are two versions available for each echo:

  • Simplified: Lightweight and ideal for fast iterations, e.g., in ChatGPT or similar interfaces.
  • PRS (Processed Response Structure): Full version with validations, expected outputs, retry logic, and detailed documentation for deeper integrations.

🚀 Starter Pack

If you're new to Echo Protocol or want a ready-to-use collection for everyday reasoning, start with the official Starter Pack.

It includes 6 core echoes:

  • 🧭 Planning
  • ✅ Coherence
  • 🔢 Prioritization
  • 🧪 Evaluation
  • ⚙️ Optimization
  • 🔁 Prompt Execution

Each one is selected for daily workflows like decision-making, troubleshooting, and organizing thought processes in tools like ChatGPT.

📄 Read the Starter Pack README →


📚 Echoes Available

Each folder contains:

  • echo-name.yaml → Simplified version
  • echo-name.prs.yaml → Full PRS version
  • README.md → Human-readable explanation
Echo Type Description
🧾 Audit Structural analysis to detect missing, redundant, or misaligned elements
Coherence Self-correction of flow when focus or purpose is lost
🤝 Consensus Negotiate between different positions to reach shared agreements
🌟 Creativity Generate diverse and divergent ideas with no initial judgment
🛠️ Diagnostic Technical analysis to detect the root of a problem
🧪 Evaluation (Structured) Critical or technical evaluation with explicit criteria, user confirmation, and recommendations
🔁 Execution (Prompt) Transform informal prompts into optimized, validated prompt flows
📘 Explanation Progressive teaching adapted to the user’s level
🧠 Generalization Extract generalizable principles from specific cases
🧿 Interpretation Semantic analysis of ambiguous or symbolic input
🧐 Metaevaluation Audit past evaluations to detect bias or improve criteria
⚙️ Optimization Refactor or improve without losing intention
🧩 Orchestration Connect multiple echoes into structured cognitive pipelines
🧭 Planification Step-by-step structure for learning or execution
🔢 Prioritization Order alternatives based on explicit decision-making criteria
🧘 Reflection Closing cycles and integrating personal change
🎭 Simulation Controlled scenario generation with internal logic

🧰 How to Use

To use any echo:

  1. Choose the simplified or PRS version inside /echoes/[type]/
  2. If you're building an AI system, use the PRS version and validate steps
  3. If you're prototyping with ChatGPT or similar, use the simplified version
  4. Check the .md file inside each folder for a human-readable explanation

🧪 Echo Template

You can create your own echoes using the official templates:


📄 Foundation & Validation

This repository is based on a formal framework that defines the Echo Protocol as a modular architecture of structured reasoning.

To understand its philosophical foundations, cognitive design principles, and the empirical validation plan, see:

👉 echo-validation.md (English) 👉 echo-validation.es.md (Español)

This document includes:

  • Definitions of what echoes are
  • Justification of their design as functional cognitive units
  • Hypotheses and metrics for empirical testing
  • Guidance for collaboration and real-world application

🤝 Contributing

Feel free to open issues or submit pull requests to expand the ecosystem.
New echoes, refinements or translations are welcome!


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A structured execution protocol for echoes in AI systems. It includes a series of echoes designed to optimize, evaluate, and plan processes in conversational AI

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