hierarchical-agent-memory

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Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.

AI & Automation 39,350 stars 6386 forks Updated today MIT

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Skill Content

# Hierarchical Agent Memory (HAM) Scoped memory system that gives AI coding agents a cheat sheet for each directory instead of re-reading your entire project every prompt. Root CLAUDE.md holds global context (~200 tokens), subdirectory CLAUDE.md files hold scoped context (~250 tokens each), and a `.memory/` layer stores decisions, patterns, and an inbox for unconfirmed inferences. ## When to Use This Skill - Use when you want to reduce input token costs across Claude Code sessions - Use when your project has 3+ directories and the agent keeps re-reading the same files - Use when you want directory-scoped context instead of one monolithic CLAUDE.md - Use when you want a dashboard to visualize token savings, session history, and context health - Use when setting up a new project and want structured agent memory from day one ## How It Works ### Step 1: Setup ("go ham") Auto-detects your project platform and maturity, then generates the memory structure: ``` project/ ├── CLAUDE.md # Root context (~200 tokens) ├── .memory/ │ ├── decisions.md # Architecture Decision Records │ ├── patterns.md # Reusable patterns │ ├── inbox.md # Inferred items awaiting confirmation │ └── audit-log.md # Audit history └── src/ ├── api/CLAUDE.md # Scoped context for api/ ├── components/CLAUDE.md └── lib/CLAUDE.md ``` ### Step 2: Context Routing The root CLAUDE.md includes a routing section that tells the agent exactly which sub...

Details

Author
sickn33
Repository
sickn33/antigravity-awesome-skills
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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