live-evo-memory

What problem does it solve?

This Skill solves the challenge of repetitive, non-deterministic task handling by maintaining a dynamic, weighted memory of task experiences that guide actions, improve consistency, and capture lessons after each task.

Core Features & Use Cases

• Always-on workflow: before every non-trivial task, retrieve relevant experiences and synthesize 3-5 actionable guidelines.
• Embedding-based retrieval and weighting: rank experiences by semantic similarity adjusted by historical weight to surface high-signal lessons.
• Lifecycle management: retrieve -> execute -> capture -> feedback; supports creating failure experiences to prevent misapplications and to refine future guidance.
• Developer tools: memory_manager.py provides init, add, search, update-weight, feedback, prune, decay, and export operations to maintain and evolve the knowledge base.

Quick Start

Initialize the memory store for your project and start applying memory-guided guidelines before every non-trivial task.