Overview
- Skill Key
- brianhearn/expertpack-export
- Author
- brianhearn
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/brianhearn/expertpack-export
- Latest Commit SHA
- 10a734764631044eda889d4e4d79615800e2fe94
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). NOT for importing/hydrating from an existing EP.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 expertpack-export 技能。 若已安装,则直接安装 expertpack-export 技能。
# ExpertPack Export
Part of the [ExpertPack](https://expertpack.ai) 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](https://expertpack.ai) · [GitHub](https://github.com/brianhearn/ExpertPack) · [Schema docs](https://expertpack.ai/#schemas)
## 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 struct...
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