quickstart.md

Quickstart

This is the fastest local proof for openclaw-mem.

Goal: show that the same query can produce a smaller, safer, cited pack once trust policy is enabled.

If you are still deciding how to adopt it, read Choose an install path first.

Prerequisites

• Python 3.10+ (recommended: Python 3.13)
• uv

1) Clone and install

git clone https://github.com/phenomenoner/openclaw-mem.git
cd openclaw-mem
uv sync --locked

2) Ingest the synthetic proof fixture

DB=/tmp/openclaw-mem-quickstart.sqlite

uv run --python 3.13 --frozen -- python -m openclaw_mem ingest \
  --db "$DB" \
  --json \
  --file ./docs/showcase/artifacts/trust-aware-context-pack.synthetic.jsonl

What this gives you:

• six synthetic rows with trust tiers, importance labels, and provenance refs
• no private or user data
• a reproducible basis for pack before/after comparison

3) Build the pack without trust gating

uv run --python 3.13 --frozen -- python -m openclaw_mem pack \
  --db "$DB" \
  --query "trust-aware context packing prompt pack receipts hostile durable memory provenance" \
  --limit 5 \
  --budget-tokens 500 \
  --trace

Expected shape:

• a compact bundle_text
• items[] + citations[]
• trace.kind = openclaw-mem.pack.trace.v1

In the synthetic proof, this ungated pack still admits one quarantined row because it matches the query text.

4) Build the pack with trust gating on

uv run --python 3.13 --frozen -- python -m openclaw_mem pack \
  --db "$DB" \
  --query "trust-aware context packing prompt pack receipts hostile durable memory provenance" \
  --limit 5 \
  --budget-tokens 500 \
  --trace \
  --pack-trust-policy exclude_quarantined_fail_open

What changes:

• the quarantined row is excluded
• a trusted row takes its place
• the pack gets smaller
• trust_policy, policy_surface, and lifecycle_shadow explain exactly what happened

5) Inspect the proof artifact

• Canonical walkthrough
• Metrics JSON
• Raw receipts

What to do next

If the local proof was enough

• move to Deployment guide
• add the sidecar to your existing OpenClaw install

If you are integrating with OpenClaw agents

• read the Agent memory skill (SOP)
• review Context pack
• review Mem Engine reference

If you want the detailed source-checkout walkthrough

• GitHub quickstart: https://github.com/phenomenoner/openclaw-mem/blob/main/QUICKSTART.md