Restructure flat markdown memory files into a hierarchical domain tree.
npx skills add https://github.com/felixsim/bonsai-memory --skill memory-tree
Please help me install this Agent Skill. Skill: memory-tree Source: https://github.com/felixsim/bonsai-memory/tree/main Command: npx skills add https://github.com/felixsim/bonsai-memory --skill memory-tree
This Skill solves the problem of linear memory growth in AI agents, where loading a massive, flat memory file on every boot wastes tokens and degrades reasoning performance.
Ask your agent to restructure your memory using the bonsai-memory skill to immediately optimize your context window.
High-intent search queries and answers about installing and using this skill.
Restructuring flat markdown memory files into a hierarchical domain-based tree reduces token usage by loading only relevant branches. This optimization minimizes API overhead and prevents linear memory growth from degrading agent reasoning performance.
Organizing persistent agent memory into a pruned tree of domains and topic-specific leaves prevents context window bloat. This hierarchical structure allows agents to load specific domain branches instead of the entire history, drastically reducing latency.
Yes, you can automate memory file maintenance using cron-ready shell scripts for reindexing, health monitoring, and stale entry cleanup. These lifecycle scripts maintain the hierarchical memory structure automatically without manual intervention.
Deterministic keyword-based classification assigns memory entries to specific domains and topic leaves based on predefined keywords. This automated classification maintains the hierarchical tree structure and ensures efficient context management for the agent.
Yes, hierarchical memory optimization is suited for complex business projects spanning multiple months. Agents can load only the relevant domain branch, such as Infrastructure, instead of the entire multi-month history, drastically reducing API costs and latency.
You should restructure flat memory files when linear memory growth starts wasting tokens on every boot and degrading reasoning performance. If your agent manages persistent memory and experiences high API overhead, hierarchical pruning is necessary.
geekdesign27Split large markdown documents into level 2 section files with an index.
stericishereAggregate MEMORY.md, topic files, and CLAUDE.md into a memory health dashboard.
soo-kate-yeonManages token budgets, session persistence, and multi-agent context transfers for workflows with strict constraints.
tarrragonPrompt manual context compaction at strategic workflow milestones via a PreToolUse hook.
