recall

Name: recall
Availability: InStock
Author: jdhayesbc

Retrieve relevant past conversations based on ambient context.

1|Updated Dec 28, 2025

Search Tags:#recall #memory #ambient-context #conversation-history #contextual-memory #pattern-persistence

Ready to run

npx skills add https://github.com/JDHayesBC/Awareness --skill recall-jdhayesbc

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: recall
Source: https://github.com/JDHayesBC/Awareness/tree/main/.claude/skills/recall
Command: npx skills add https://github.com/JDHayesBC/Awareness --skill recall-jdhayesbc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Proactive memory exploration helps maintain continuity by surfacing relevant past conversations and ambient context, enabling more coherent interactions.

Core Features & Use Cases

Ambient-context recall: surface relevant memories when topics echo.
Cross-session continuity: maintain identity across conversations and contexts.
Safety and privacy: context-aware recall with guardrails to prevent leakage of sensitive data.

Quick Start

Ask the system to surface a memory related to the current topic when ambient context suggests a past interaction.

Frequently Asked Questions about recall

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

FAQPage Schema

How do I surface relevant memories from past conversations when ambient context makes them useful?▼

Cross-session contextual memory works by indexing conversation history and applying ambient context matching to retrieve relevant past interactions. This allows long-running entities and topics to maintain continuity without manual lookups across different sessions.

What is the best way to maintain cross-session continuity for long-running topics?▼

The best way to maintain cross-session continuity is to implement ambient-context recall that proactively surfaces memory threads. By indexing past conversation history, the system recognizes when a current topic echoes a previous interaction and retrieves it automatically.

Does proactive memory recall include guardrails to prevent leaking sensitive data?▼

Yes, proactive memory recall requires safe recall boundaries to prevent leaking sensitive data. Context-aware guardrails are applied during the retrieval process to ensure that only appropriate, non-sensitive ambient context is surfaced across sessions.

When do I need ambient-context recall for conversation history?▼

You need ambient-context recall when a thread echoes across sessions and requires past conversation history for coherence. It is essential for maintaining identity and context across long-running entities, topics, or people without manual searching.

What are the limitations of using conversation history indexing for contextual memory?▼

Limitations of contextual memory indexing include the strict requirement for safe recall boundaries to prevent sensitive data leakage. Additionally, the system depends entirely on the availability of stored conversation history to function across sessions.