recall

Retrieve project-specific memories and synthesize a concise markdown summary.

4|1|Updated Mar 14, 2026
One-click install
npx skills add https://github.com/MattVOLTA/outworkos_diy --skill recall-mattvolta
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: recall
Source: https://github.com/MattVOLTA/outworkos_diy/tree/main/skills/plugins/memory-system/skills/recall
Command: npx skills add https://github.com/MattVOLTA/outworkos_diy --skill recall-mattvolta

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Retrieving and summarizing memories from the central database to provide timely, contextual awareness for the current project.

Core Features & Use Cases

  • Query memories table for project-specific entries and exclude deprecated or low-confidence items.
  • Synthesize results into a concise, readable context summary for immediate use in a session.
  • Use at session start or on-demand when historical context is needed.

Quick Start

Ask memory to recall the most relevant project memories to inform the current context.

Frequently Asked Questions about recall

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

FAQPage Schema
How do I retrieve project context from a database of past memories?

Recall retrieves project context by querying the memories table for project-specific entries and synthesizing them into a concise summary. It automatically filters out deprecated or low-confidence items to deliver reliable historical context for your session.

What is memory synthesis and how does it work for project context?

Memory synthesis for project context works by querying non-deprecated memories from a central database and using a memory-retriever agent to synthesize results. It presents a readable markdown summary to inform your current session context.

When do I need to query past memories for a project session?

You need to query past memories at the start of a session or on-demand when historical context is required. Retrieving synthesized memories provides timely contextual awareness for the current project from a central database.

How to exclude deprecated or low-confidence entries when retrieving project memories?

To exclude deprecated or low-confidence entries when retrieving project memories, the system filters the memories table during the query phase. It specifically queries non-deprecated memories and uses a memory-retriever agent to synthesize only high-confidence results.

What happens if no memories exist when querying project context?

If no memories exist when querying project context, the system presents a clear fallback message. The memory-retrieval process checks the database for non-deprecated entries and outputs markdown with a fallback notification when the query returns empty.

Can I use memory retrieval to inform current project context on-demand?

Yes, you can use memory retrieval to inform current project context on-demand. The system queries the central database for project-specific memories, synthesizes the results into a concise summary, and presents the context whenever historical awareness is needed.