ham
Set up Hierarchical Agent Memory (HAM) — scoped CLAUDE.md files per directory that reduce token spend. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop",
What it does
Pro Guard — run FIRST
Before ANY command, check for Pro signals: .ham/config.json with "pro": true, enabledImporters with more than "claude", or any **/AGENTS.md files.
- If Pro detected: allow
go ham(Pro-aware mode) andham remove(has own Pro logic). All other commands → printHAM Pro detected — this project is managed by HAM Pro. Manage at goham.devand STOP. - Pro rules: NEVER create/modify/delete AGENTS.md files. CLAUDE.md = HAM-owned. AGENTS.md = Pro-owned.
Commands
Trigger: "ham commands" or "ham help" — list all commands:
| Command | What it does |
|---|---|
go ham | Set up HAM (auto-detects stack and structure) |
ham remove | Remove HAM safely (preserves Pro files) |
ham update | Run bash <skill-dir>/scripts/update.sh, update .ham/version |
ham status | Show version, update status, memory file count, last setup date |
ham route | Add/update Context Routing in root CLAUDE.md |
ham dashboard | Launch web dashboard at :7777 via node <skill-dir>/dashboard/launch.js --port 7777 |
ham savings | Show token and cost savings report |
ham carbon | Run node <skill-dir>/dashboard/carbon-cli.js [--last] [--days 30] |
ham insights | Generate insights → write actionable items to .memory/inbox.md |
ham benchmark | Run node <skill-dir>/dashboard/benchmark-cli.js [--days 30] [--model name] [--json] |
ham baseline start | Begin 10-task baseline capture |
ham baseline stop | End baseline early, keep partial data |
ham metrics clear | Delete all benchmark data (confirm first) |
ham audit | Check memory system health |
ham sync | Sync Claude Code sessions → .ham/metrics/sessions.jsonl. Run node <skill-dir>/dashboard/sync-cli.js [--force] [--json] |
go ham — Setup
- Update check — compare
.ham/versionagainstham_versionin frontmatter. If outdated, print update notice. Never block. - Detect platform — scan for:
*.xcodeproj/Package.swift(iOS),build.gradle*(Android),pubspec.yaml(Flutter),package.json+ framework (Web/RN),pyproject.toml/requirements.txt(Python),Cargo.toml(Rust),go.mod(Go). - Detect maturity — count subdirs with code: 0-2 = greenfield, 3+ = brownfield.
- Monorepo guard — if >20 code dirs: present sorted list, pre-select top 15, let user adjust. Hard cap: never create >20 subdirectory CLAUDE.md files.
- Generate files silently, then confirm.
Pro-aware mode: if Pro detected, skip directories with existing CLAUDE.md (Pro-created). Fill gaps only. Never touch AGENTS.md.
Generated Structure
project/
├── CLAUDE.md # Root (~200 tokens)
├── .ham/
│ ├── version
│ └── metrics/state.json # {mode, tasks_completed, tasks_target, started_at, memory_reads, total_prompts}
├── .memory/
│ ├── decisions.md # ADRs
│ ├── patterns.md # Reusable patterns
│ ├── inbox.md # Inferred items (brownfield only)
│ └── audit-log.md # Audit history (last 5 entries)
└── [src dirs]/CLAUDE.md # Per-directory (brownfield only)
Greenfield: root + .memory/ + .ham/ only. Brownfield: also subdirectory CLAUDE.md files.
.gitignore
Append (idempotent — check for # HAM marker first):
# HAM — AI agent scaffolding (local, do not commit)
.ham/
.memory/
**/CLAUDE.md
!CLAUDE.md
# end HAM
Capture Baseline
Before creating files, save .memory/baseline.json:
{"captured_at":"YYYY-MM-DD","existing_claude_md":{"found":true,"chars":4820,"tokens":1205},"notes":"Migrated from monolithic CLAUDE.md"}
If no existing CLAUDE.md: {"captured_at":"...","existing_claude_md":{"found":false},"estimated_baseline_tokens":7500}.
Initialize Benchmarking
Create .ham/metrics/state.json: {"mode":"baseline","tasks_completed":0,"tasks_target":10,"started_at":"ISO-8601","memory_reads":0,"total_prompts":0}. Next 10 tasks log to baseline.jsonl without HAM memory loading. Auto-transitions to active after 10.
Confirm Setup
Report files created. If root CLAUDE.md >3,000 tokens: warn, list sections that may belong in subdirectory files, offer interactive migration (present each candidate one at a time, move only on user confirmation).
Operating Instructions
Embed in every root CLAUDE.md:
## Agent Memory System
### Before Working
- Read this file for global context, then read the target directory's CLAUDE.md before changes
- If this file has a ## Context Routing section, use it to find the right subdirectory CLAUDE.md
- Check .memory/decisions.md before architectural changes
- Check .memory/patterns.md before implementing common functionality
- Check if audit is due: if 14+ days or 10+ sessions since last audit in .memory/audit-log.md, suggest running one
### During Work
- Create CLAUDE.md in any new directory you create
### After Work
- Update relevant CLAUDE.md if conventions changed
- Log decisions to .memory/decisions.md (ADR format)
- Log patterns to .memory/patterns.md
- Uncertain inferences → .memory/inbox.md (never canonical files)
### Safety
- Never record secrets, API keys, or user data
- Never overwrite decisions — mark as [superseded]
- Never promote from inbox without user confirmation
Task Metrics Logging
Each non-trivial task logs two JSONL entries to .ham/metrics/tasks.jsonl (or baseline.jsonl in baseline mode):
{"id":"task-<hex8>","type":"task_start","timestamp":"ISO-8601","description":"...","ham_active":true,"model":"claude-opus-4-6","files_read":0,"memory_files_loaded":0,"estimated_tokens":0}
{"id":"task-<hex8>","type":"task_end","timestamp":"ISO-8601","status":"completed"}
Skip trivial queries (HAM commands, yes/no, clarifications). Increment total_prompts in state.json for every non-trivial task; increment memory_reads when .memory/ files are loaded.
Baseline Mode
Check .ham/metrics/state.json before each task:
-
mode = "baseline": write to
baseline.jsonl, setham_active: false, skip subdir CLAUDE.md and .memory/ files. Only incrementtasks_completedforstatus: "completed"(not "error"/"skipped"). Transition to active whentasks_completed >= tasks_target. -
mode = "active", or state.json missing, or state.json unparseable: write to
tasks.jsonl, setham_active: true, load all files normally. If state.json was corrupt, warn user once:⚠ .ham/metrics/state.json is corrupted. Treating as active mode.
ham savings
Trigger: "HAM savings" or "HAM stats"
Read .memory/baseline.json, count tokens in all CLAUDE.md and .memory/ files (chars ÷ 4), then display: baseline section, current HAM setup, tokens per prompt, savings, and monthly projection (1,500 prompts at $3/M Sonnet, $15/M Opus).
Calculation
root_tokens = count_tokens(read("CLAUDE.md"))
subdir_files = glob("**/CLAUDE.md", exclude="root")
avg_subdir = sum(count_tokens(read(f)) for f in subdir_files) / len(subdir_files) if subdir_files else 0
# .memory/ weighted by tracked read frequency
memory_tokens = sum(count_tokens(read(f)) for f in glob(".memory/*.md"))
state = read_json(".ham/metrics/state.json")
memory_weight = state["memory_reads"] / state["total_prompts"] if state.get("total_prompts", 0) >= 10 else 0.30
ham_tokens = root_tokens + avg_subdir + (memory_tokens * memory_weight)
# Baseline: measured if baseline.json exists, tiered estimate otherwise
if exists(".memory/baseline.json"):
baseline_mid = baseline_data["old_claude_md_tokens"] + max(500, len(subdir_files) * 300)
baseline_is_measured = True
else:
code_dirs = count_dirs_with_code()
baseline_mid = max(1000, ham_tokens * 1.5) if code_dirs <= 2 else max(3000, ham_tokens * 2.5) if code_dirs <= 10 else max(5000, ham_tokens * 3.5)
baseline_is_measured = False
Display rules: when baseline_is_measured = False, show raw token counts only — no savings percentage or cost projections. Add: ⚠ No baseline captured — savings % requires a real baseline. Run "go ham" to capture one. Show "(estimated)" next to .memory/ frequency until 10+ prompts tracked.
ham remove
Trigger: "ham remove" — EXEMPT from Pro guard.
- Detect Pro (same checks as guard)
- Inventory: skill-owned (.memory/*, .ham/*, subdir CLAUDE.md, HAM sections in root) vs Pro-owned (.ham/config.json, AGENTS.md) vs user files (root CLAUDE.md content)
- Show dry-run listing what will be deleted/edited/kept
- Confirm with user
- Execute: delete skill files, strip
## Agent Memory Systemand## Context Routingfrom root CLAUDE.md, remove HAM block from .gitignore - Report results
ham route
Trigger: "ham route"
- Find all
**/CLAUDE.md(excluding root) - Build entries:
→ [label]: [path](label = directory name) - Append or update
## Context Routingin root CLAUDE.md. Never remove existing entries.
ham dashboard
Trigger: "HAM dashboard" or "HAM sandwich"
Check for updates, then run node <skill-dir>/dashboard/launch.js --port 7777 from the project root. Dashboard reads session JSONL from ~/.claude/projects/ — no database. Tell user to open http://localhost:7777.
ham insights
Trigger: "HAM insights"
Run node <skill-dir>/dashboard/insights-cli.js --days 30. Parse JSON output, filter to actionable items, deduplicate against existing .memory/inbox.md, write new items in format:
### Insight: [title] ([date])
**Confidence:** [severity] | **Observed:** [detail] | **Proposed Action:** [action]
Log to .memory/audit-log.md (keep last 5 entries). Report summary to user.
ham audit
Trigger: "HAM audit" or "HAM health"
Check: root CLAUDE.md size (recommend <60 lines, <250 tokens), subdirectory file count and oversized files (>75 lines), missing CLAUDE.md in code dirs, .memory/ entry counts, unreviewed inbox items. Present results, append to .memory/audit-log.md.
ham baseline start / stop
start: Create .ham/metrics/state.json with mode: "baseline", tasks_target: 10. Tell user next 10 tasks capture baseline.
stop: Set mode: "active" in state.json. Report tasks captured.
Templates
See templates.md for full templates. Summary:
- Root CLAUDE.md: Project name, Stack, Rules, Agent Memory System (operating instructions above)
- Subdirectory CLAUDE.md: Purpose (1 sentence), Conventions, Patterns
- decisions.md: ADR format (status, decision, context, alternatives)
- inbox.md: Header + review instructions
Capabilities
Install
Quality
deterministic score 0.48 from registry signals: · indexed on github topic:agent-skills · 53 github stars · SKILL.md body (10,458 chars)