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+---
+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:
+
+```markdown
+## 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 audit` every 2 weeks to catch stale or missing context files
+- Use `ham route` after adding new directories to keep routing current
+- Review `.memory/inbox.md` periodically — 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 patterns
+- `agent-memory-mcp` — MCP-based memory integration