echo

Retrieve historical AI session data via semantic vector and keyword search.

412|45|Updated Feb 19, 2026

Search Tags:#context #recall #search #memory #history #sessions

Ready to run

npx skills add https://github.com/cwinvestments/memstack --skill echo-cwinvestments

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: echo
Source: https://github.com/cwinvestments/memstack/tree/main/skills/echo
Command: npx skills add https://github.com/cwinvestments/memstack --skill echo-cwinvestments

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill retrieves information from past AI sessions, preventing the need to manually search through old logs or rely on fragmented memory.

Core Features & Use Cases

Semantic Search: Finds relevant past conversations based on the meaning of your query, not just keywords.
Multi-Source Recall: Combines results from vector databases, SQLite, and markdown files for comprehensive recall.
Use Case: If you're unsure about a decision made in a previous project session, you can ask "What did we decide about the database schema last week?" and Echo will find the exact log entry.

Quick Start

Use the echo skill to search for information about the 'user authentication' feature from past sessions.

Frequently Asked Questions about echo

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

FAQPage Schema

How do I recall past AI session history without manually searching logs?▼

To recall past AI session history, this Skill retrieves past interactions using semantic vector search and keyword-based database queries. It combines LanceDB vector embeddings and SQLite structured data to find exact log entries from previous sessions.

Can I search past session context using semantic vector search instead of exact keywords?▼

Yes, you can search past session context using semantic vector search. This Skill leverages LanceDB to find relevant past conversations based on the meaning of your query, ensuring comprehensive recall across multiple sessions and projects.

How do I retrieve specific decisions and tasks from previous project sessions?▼

To retrieve specific decisions and tasks from previous project sessions, query the stored historical session data. This Skill supports recall of accomplished tasks and pending items across multiple projects using SQLite and markdown file fallbacks.

Does this session recall tool work with LanceDB and SQLite for data storage?▼

Yes, this session recall tool works with LanceDB and SQLite. It leverages LanceDB for vector embeddings and SQLite for structured data queries, while also using markdown files as a fallback for comprehensive historical data retrieval.

What is the best way to search historical AI interactions across multiple projects?▼

The best way to search historical AI interactions across multiple projects is using a multi-source recall approach. This Skill combines vector database results, SQLite queries, and markdown file fallbacks to find relevant past conversations based on semantic meaning.

What are the limitations of using markdown files for session memory recall?▼

Using markdown files for session memory recall is limited to a fallback mechanism. The primary recall system leverages LanceDB vector embeddings and SQLite structured data, meaning markdown fallbacks may lack the semantic search depth of the database queries.