recall

Search memory files to retrieve and rank past experiences and learnings.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/Ayub-Khan/immortal_agent_swarm --skill recall-ayub-khan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: recall
Source: https://github.com/Ayub-Khan/immortal_agent_swarm/tree/main/.agents/skills/recall
Command: npx skills add https://github.com/Ayub-Khan/immortal_agent_swarm --skill recall-ayub-khan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Recall skill enables agents to search and retrieve information from memory files, supporting both self-recall during tasks and cross-agent memory queries to improve collaboration and decision making.

Core Features & Use Cases

  • Self-Recall: Search experiences and learnings in memory to apply past learnings to current tasks.
  • Cross-Agent Query: Respond to memory requests from other agents to synthesize collective context.
  • Information Synthesis & Relevance: Rank and merge memory findings to provide coherent guidance.

Quick Start

Ask the agent to recall relevant experiences and learnings from memory to inform the task at hand.

Frequently Asked Questions about recall

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

FAQPage Schema
How do I search memory files to retrieve past learnings for a current task?

To retrieve past learnings, search memory files using the recall skill to find relevant experiences and relationships, which then ranks and merges findings to provide coherent guidance for your current task.

What is cross-agent memory query and how does it improve collaboration?

Cross-agent memory query is a mechanism where agents request and retrieve memory from one another to synthesize collective context, improving collaboration and decision making across multiple agents.

Can I apply self-recall during task execution to inform current decisions?

Yes, you can apply self-recall during task execution by asking the agent to search its memory files for relevant experiences, learnings, and relationships to inform current decisions.

What's the best way to synthesize information from multiple memory experiences?

The best way to synthesize information from multiple memory experiences is to use the recall skill, which ranks and merges memory findings to provide structured, coherent guidance for effective decision making.

Do I need any specific dependencies to perform cross-agent memory queries?

No specific dependencies are required to perform cross-agent memory queries, as the recall skill operates independently to search memory files and retrieve relevant information from past experiences.