Hierarchical Agent Memory is a automation claude skill built by sickn33. Best for: Development teams using Claude Code reduce input tokens by 90%+ by structuring project memory hierarchically instead of re-reading entire codebases per session..
- What it does
- Reduce token spend by organizing project context into scoped CLAUDE.md files with routing, dashboards, and audit tracking.
- Category
- automation
- Created by
- sickn33
- Last updated
Hierarchical Agent Memory
Reduce token spend by organizing project context into scoped CLAUDE.md files with routing, dashboards, and audit tracking.
Skill instructions
name: hierarchical-agent-memory description: "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." risk: safe source: "https://github.com/kromahlusenii-ops/ham" date_added: "2026-02-27"
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-context to load:
## Context Routing
→ api: src/api/CLAUDE.md
→ components: src/components/CLAUDE.md
→ lib: src/lib/CLAUDE.md
The agent reads root, then immediately loads the relevant subdirectory context — no guessing.
Step 3: Dashboard ("ham dashboard")
Launches a web dashboard at localhost:7777 that visualizes:
- Token savings (HAM-on vs HAM-off sessions)
- Daily token and cost trends
- Per-directory session breakdown
- Context file health (missing/stale/inherited CLAUDE.md coverage)
- Routing compliance (how often the agent follows the routing map)
- Carbon/energy estimates
Commands
| Trigger | What it does |
|---|---|
| go ham | Set up HAM — auto-detect platform, generate CLAUDE.md files |
| ham savings | Show token and cost savings report |
| ham dashboard | Launch the interactive web dashboard |
| ham audit | Health check on memory files |
| ham insights | Generate actionable insights from session data |
| ham route | Add/update Context Routing section in root CLAUDE.md |
| ham carbon | Show energy and carbon efficiency data |
Examples
Example 1: First-time setup
User: go ham
Agent: HAM setup complete. Created 8 files.
- CLAUDE.md (root)
- .memory/decisions.md
- .memory/patterns.md
- .memory/inbox.md
- src/api/CLAUDE.md
- src/components/CLAUDE.md
- src/lib/CLAUDE.md
- src/utils/CLAUDE.md
Baseline captured in .memory/baseline.json
Run "HAM savings" to see your token and cost savings.
Example 2: Checking savings
User: ham savings
Agent:
Before HAM: ~7,500 tokens/prompt
After HAM: ~450 tokens/prompt
Savings: 7,050 tokens (94%)
Monthly projection (1,500 prompts):
Sonnet: ~$31.73 saved
Opus: ~$158.63 saved
Best Practices
- Keep root CLAUDE.md under 60 lines / 250 tokens
- Keep subdirectory CLAUDE.md files under 75 lines each
- Run
ham auditevery 2 weeks to catch stale or missing context files - Use
ham routeafter adding new directories to keep routing current - Review
.memory/inbox.mdperiodically — confirm or reject inferred items
Limitations
- Token estimates use ~4 chars = 1 token approximation, not a real tokenizer
- Baseline savings comparisons are estimates based on typical agent behavior
- Dashboard requires Node.js 18+ and reads session data from
~/.claude/projects/ - Context routing detection relies on CLAUDE.md read order in session JSONL files
- Does not auto-update subdirectory CLAUDE.md content — you maintain those manually or via
ham audit - Carbon estimates use regional grid averages, not real-time energy data
Related Skills
agent-memory-systems— general agent memory architecture patternsagent-memory-mcp— MCP-based memory integration
Use this skill
Most skills are portable instruction packages. Claude Code supports SKILL.md directly. Other agents can use adapted files like AGENTS.md, .cursorrules, and GEMINI.md.
Claude Code
Save SKILL.md into your Claude Skills folder, then restart Claude Code.
mkdir -p ~/.claude/skills/hierarchical-agent-memory && curl -L "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/HEAD/skills/hierarchical-agent-memory/SKILL.md" -o ~/.claude/skills/hierarchical-agent-memory/SKILL.mdInstalls to ~/.claude/skills/hierarchical-agent-memory/SKILL.md.
Use cases
Development teams using Claude Code reduce input tokens by 90%+ by structuring project memory hierarchically instead of re-reading entire codebases per session.
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Creator
Ssickn33
@sickn33