Expertpack Export

Export an OpenClaw instance's accumulated knowledge into a structured ExpertPack composite. Use when backing up an agent's identity, exporting for migration, or creating a portable knowledge snapshot. Handles auto-discovery (scanning workspace state to identify constituent packs), distillation (compressing raw state into structured EP files), and packaging (writing EP-compliant packs + composite manifest). Output is Obsidian-compatible — includes YAML frontmatter on all content files and can be opened as an Obsidian vault. NOT for importing/hydrating from an existing EP.

Part of the ExpertPack framework — a structured, portable knowledge format for AI agents.

Export an OpenClaw instance into a composite ExpertPack — an agent pack (subtype: agent) as the voice, plus person/product/process packs as knowledge constituents.

Learn more: expertpack.ai · GitHub · Schema docs

Prerequisites

• Read references/schemas-summary.md for the EP schema rules this export must follow.
• The export writes to a target directory (default: {workspace}/export/). It does NOT modify the agent's live workspace files.

Export Flow

1. Scan

Run scripts/scan.py to inventory the workspace. It outputs a JSON manifest of discovered files, their categories, and proposed pack assignments.

bash

python3 {skill_dir}/scripts/scan.py --workspace /root/.openclaw/workspace --output /tmp/ep-scan.json

Review the scan output. It proposes:

• Which files map to which pack type (agent, person, product, process)
• Which knowledge domains were detected
• Confidence scores for ambiguous classifications

2. Propose

Present the proposed composite to the user:

• List each proposed pack with type, slug, and key content sources
• Flag ambiguous classifications for user decision
• Note any gaps (e.g., "No process packs detected — skip or create stubs?")

Wait for user confirmation before proceeding.

3. Distill

Run scripts/distill.py for each proposed pack. It reads source files, extracts knowledge, deduplicates, and writes EP-compliant output.

bash

python3 {skill_dir}/scripts/distill.py \
  --scan /tmp/ep-scan.json \
  --pack agent:easybot \
  --output /root/.openclaw/workspace/export/packs/easybot/

Repeat for each pack. The script:

• Reads source files listed in the scan manifest
• Extracts and classifies knowledge assertions
• Deduplicates (prefers newest for conflicts)
• Writes structured .md files with proper headers and frontmatter
• Writes manifest.yaml per pack
• Strips secrets (API keys, tokens, passwords) automatically

4. Compose

Run scripts/compose.py to generate the composite manifest and overview.

bash

python3 {skill_dir}/scripts/compose.py \
  --scan /tmp/ep-scan.json \
  --export-dir /root/.openclaw/workspace/export/

5. Validate

Run scripts/validate.py to check the export against schema rules.

bash

python3 {skill_dir}/scripts/validate.py --export-dir /root/.openclaw/workspace/export/

It checks:

• All required files exist per schema
• manifest.yaml fields are valid
• No secrets leaked (scans for API key patterns)
• File sizes within guidelines
• Cross-references resolve

6. Review & Ship

Present the validation report and a summary of what was exported. The user decides whether to commit/push or adjust.

Important Rules

• Never include secrets. The scan and distill scripts strip known patterns, but always review operational/tools.md and operational/infrastructure.md manually.
• Distill, don't copy. Raw journal entries and session states should be compressed into structured knowledge. The export should be 10-20% the volume of raw state.
• Respect privacy. Flag personal information about the user for access tier review. Default user-specific content to private access.
• Preserve provenance. Each distilled file should note its source files in frontmatter.
• Don't modify the live workspace. All output goes to the export directory.