Claw memory manager

Claw Memory Manager

• Version: 1.1.1
• License: MIT
• Author: Evan Song · github.com/Songhonglei
• Repository: https://github.com/Songhonglei/better-agent-skills

Manage OpenClaw Agent's built-in memory features through one safe CLI: enable/disable, tune parameters, preview with dry-run, auto-backup, and auto-restart.

What it does

OpenClaw Agent has two built-in memory features:

1. Dreaming — scheduled job (default 03:00 local time) that scans your daily memory signals, scores them, and auto-promotes high-recall items to long-term MEMORY.md.
2. Active Memory — lightweight sub-agent that runs before every turn, retrieves relevant memories, and injects them into the model context window for better recall.

Both require editing nested config trees, syncing to multiple paths in managed environments, and restarting the gateway. This skill does it all in one command, safely.

Supported features

Feature	What	CLI flags
dreaming	Light→REM→Deep three-phase memory consolidation	--half-life, --max-age, --timezone
active-memory	Proactive memory injection with style presets	--style {conservative,balanced,aggressive}

See references/features.md for full schema details.

Quick start — Dreaming

# Check OpenClaw support
python3 scripts/agent_memory.py check dreaming

# See current state
python3 scripts/agent_memory.py status dreaming

# Enable with defaults (half-life 30d, max-age 60d, timezone UTC)
python3 scripts/agent_memory.py enable dreaming

# Custom tuning
python3 scripts/agent_memory.py enable dreaming --half-life 14 --timezone America/New_York

# Preview only
python3 scripts/agent_memory.py enable dreaming --dry-run

# Disable
python3 scripts/agent_memory.py disable dreaming

Quick start — Active Memory

# Enable with default style (balanced)
python3 scripts/agent_memory.py enable active-memory

# Pick a style preset
python3 scripts/agent_memory.py enable active-memory --style conservative
python3 scripts/agent_memory.py enable active-memory --style aggressive

# Inspect current style + parameters
python3 scripts/agent_memory.py status active-memory

# Preview only
python3 scripts/agent_memory.py enable active-memory --style aggressive --dry-run

# Disable
python3 scripts/agent_memory.py disable active-memory

Active Memory style presets

Style	Use case	queryMode	promptStyle	Context window	Inject cap	Timeout	Thinking
conservative	Fastest, precision-focused	message	precision-heavy	user 1×120 / assist 0	150 chars	8 s	off
balanced (default)	Everyday use	recent	balanced	user 2×220 / assist 1×180	220 chars	15 s	off
aggressive	Best recall, larger context	full	recall-heavy	user 4×500 / assist 2×400	500 chars	25 s	minimal

Style is inferred back from queryMode when running status active-memory.

CLI flags

Flag	Applies to	Purpose	Default
--half-life N	dreaming	Signal decay half-life (1-90 days)	30
--max-age N	dreaming	Signal hard expiry (1-90 days)	60
--timezone TZ	dreaming	IANA timezone for schedule	UTC
--style NAME	active-memory	conservative / balanced / aggressive	balanced
--dry-run	all	Print planned changes; do not write	off
--no-backup	all	Skip *.bak.<timestamp> creation	off (backup on)
--no-restart	all	Skip openclaw gateway restart after change	off (auto-restart on)

Safety features

Layer	Behavior
Auto-backup	Every write creates openclaw.json.bak.<YYYYMMDD_HHMMSS> (use --no-backup to opt out)
Dry-run	--dry-run prints exact JSON change + sync targets + restart action without touching disk
Managed-env auto-detect	/app/clawconfig/ and /app/k8s-config/clawconfig/ auto-detected — synced if present, silently skipped if not
Validation	Half-life and max-age ranges enforced (1-90); --style enforced by argparse choices
Verify after write	Re-reads config to confirm change took effect before reporting success

Configuration sources

The script reads/writes:

1. Runtime config: ~/.openclaw/openclaw.json (or $OPENCLAW_CONFIG)
2. Managed-environment mirrors (auto-detected, optional):
   • /app/clawconfig/openclaw.json (Pod restart source in K8s)
   • /app/k8s-config/clawconfig/openclaw.json (K8s ConfigMap source)

If you run OpenClaw locally (e.g. npm install -g openclaw on your laptop), only the runtime config exists and the script does the right thing automatically.

Why use this skill

Without this skill, enabling Active Memory requires:

1. Reading the OpenClaw plugins config schema
2. Editing nested JSON under plugins.entries.active-memory with 10+ fields
3. Picking sensible defaults for queryMode / promptStyle / context windows
4. Copying to 2 mirror paths (in K8s environments)
5. Running openclaw gateway restart
6. Manually verifying

This skill: one command + a style preset, with backup + dry-run + verify built in.

Extending to new memory features

Add a new entry to the FEATURES dict at the top of agent_memory.py:

FEATURES["my-feature"] = {
    "path": ["plugins", "entries", "my-plugin", "config"],
    "enable_patch": {"enabled": True, ...},
    "disable_patch": {"enabled": False},
    "check_key": "enabled",
    "status_key": "frequency",  # field shown in `status`
    "description": "What this feature does",
}

For features with preset-style choices (like active-memory), follow the ACTIVE_MEMORY_STYLES pattern and set supports_style: True in the entry.

Files

claw-memory-manager/
├── SKILL.md              ← agent entry point
├── README.md             ← this file
├── LICENSE               ← MIT
├── .gitignore
├── scripts/
│   └── agent_memory.py   ← single Python entry, zero external deps
└── references/
    └── features.md       ← feature catalog + schema reference

Changelog

See CHANGELOG.md for the full version history.

See also

• references/features.md — full feature catalog, config schemas, and extension guide
• OpenClaw docs — platform reference