From memanto
MEMANTO Cookbooks provides complete implementation guides for building AI applications with persistent memory. Each cookbook is a production-ready blueprint covering architecture, setup, and working code.
How this skill is triggered — by the user, by Claude, or both
Slash command
/memanto:memanto-cookbooksThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
MEMANTO Cookbooks provides complete implementation guides for building AI applications with persistent memory. Each cookbook is a production-ready blueprint covering architecture, setup, and working code.
MEMANTO Cookbooks provides complete implementation guides for building AI applications with persistent memory. Each cookbook is a production-ready blueprint covering architecture, setup, and working code.
Users without an account should register at console.moorcheh.ai to create a free Moorcheh account and obtain an API key.
Before starting any cookbook project, review:
Full end-to-end setup for an AI agent with long-term memory across sessions. Covers agent creation, session management, the session-start recall pattern, proactive memory storage, and MEMORY.md sync. The foundation for all other cookbooks.
How to resume exactly where you left off across sessions and agent restarts. Covers session token lifecycle, MEMORY.md as the cold-start snapshot, commitment tracking, and context summarization.
Export, visualize, and audit all agent memories. Covers markdown export, timeline visualization, confidence filtering, tag-based audits, and memory pruning.
Set up automated daily memory digests on a schedule. Covers cron-based scheduling, the daily summary service, summary content structure, and reading summaries in context.
Build a question-answering system grounded in agent memory. Covers the memanto answer RAG pipeline, context window management, and citation tracking.
npx claudepluginhub moorcheh-ai/memanto-agent-skillsCreates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.