Search cross-agent memories with keyword and date filters.
npx skills add https://github.com/michaelneale/megamind --skill remember-michaelneale
Please help me install this Agent Skill. Skill: remember Source: https://github.com/michaelneale/megamind/tree/main Command: npx skills add https://github.com/michaelneale/megamind --skill remember-michaelneale
Cross-agent memory recall across Goose, Claude Code, Pi, Codex, Gemini, Amp, and OpenCode to keep contexts in sync and avoid repeating discussions.
Ask me to recall past conversations across your agents and I will return matching memories.
High-intent search queries and answers about installing and using this skill.
To recall past conversations across different coding agents, you can search cross-agent memories to retrieve relevant histories. This surfaces past decisions and code references to keep contexts in sync when switching tools.
Yes, you can search conversation history from Claude Code, Gemini, Goose, Pi, Codex, Amp, and OpenCode simultaneously. The search applies across these sources to surface relevant context and avoid repeating discussions.
You filter agent memory search results by applying keyword and date range filters. You can also control per-source limits and use both AND/OR modes to narrow down the retrieved cross-agent conversations.
Yes, cross-agent memory search caches results. It returns structured results designed for human review or machine parsing, improving retrieval speed for relevant conversations across your coding agents.
The best way to keep context in sync when switching AI coding tools is to search cross-agent memories. This allows you to quickly recall past decisions, code references, and conversations across multiple agent histories.
Cross-agent memory search returns structured results that support both human review and machine parsing. It applies keyword and date filters across multiple sources and caches the output for efficient retrieval.
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