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Openclaw User Data Pack

v1.0.5

Agent instructions: pack/apply OpenClaw user data via scripts; overwrite-by-path only. You dry-run first, read EXPORT_MANIFEST.txt, gate optional layers, res...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for zhaobudaoyuema/openclaw-user-data-pack.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Openclaw User Data Pack" (zhaobudaoyuema/openclaw-user-data-pack) from ClawHub.
Skill page: https://clawhub.ai/zhaobudaoyuema/openclaw-user-data-pack
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install openclaw-user-data-pack

ClawHub CLI

Package manager switcher

npx clawhub@latest install openclaw-user-data-pack
Security Scan
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description match the actual files and behavior: pack_openclaw.py builds a zip with EXPORT_MANIFEST.txt and apply_openclaw.py extracts files into workspace and ~/.openclaw paths. Required capabilities are proportional — no unrelated credentials, binaries, or config paths are demanded.
Instruction Scope
SKILL.md gives precise runtime instructions (dry-run first, read EXPORT_MANIFEST.txt, gate optional layers, require explicit consent for sessions/config/managed-skills). The instructions only reference files the tool legitimately needs (workspace, openclaw.json, zip manifest). They explicitly forbid writing credentials/credential dirs and emphasize backups and user confirmation for sensitive layers.
Install Mechanism
There is no registry install spec (instruction-only install), but SKILL.md tells the agent to run `pip install -r requirements.txt` as needed. The requirements are minimal (json5). This is expected but means the agent will fetch a PyPI package if it runs that step — moderate risk compared with an all-local instruction-only skill; however the included Python scripts are present in the package and do not download arbitrary code themselves.
Credentials
The skill requests no secret env vars and only uses OPENCLAW_HOME / optional OPENCLAW_PROFILE for normal path resolution. It warns that openclaw.json may contain tokens/secrets and requires explicit opt-in to include/restore that config. The scripts intentionally avoid ~/.openclaw/credentials and perform path-safety checks.
Persistence & Privilege
Skill is not always-enabled and is user-invocable. It does not modify other skills or system-wide config beyond writing into the user's OpenClaw directories when invoked. Autonomous invocation is allowed by platform default but not combined with other concerning privileges here.
Assessment
This skill appears to do what it says: create/export a zip with EXPORT_MANIFEST.txt and extract it back into OpenClaw dirs. Before using it: always run the scripts with --dry-run first and inspect EXPORT_MANIFEST.txt inside the produced zip; back up the target OpenClaw home/workspace (only openclaw.json gets an automatic .bak timestamped file when restored); do not enable sessions or config snapshot flags unless you understand they may include full chat transcripts or tokens; only apply zips from trusted sources. Note that following SKILL.md will require running `pip install -r requirements.txt` which fetches json5 from PyPI — if you or your agent run that, understand it performs a network package install. If you want extra safety, inspect the provided Python scripts locally before running them and run pack/apply on a throwaway copy first.

Like a lobster shell, security has layers — review code before you run it.

latestvk97bssp9bn748jbc0f7ys2ty49838h6z
214downloads
0stars
5versions
Updated 22h ago
v1.0.5
MIT-0

OpenClaw agent: pack and apply user data

Who reads this: you are the OpenClaw agent (runtime). This file is not end-user documentation—it tells you what to run, what to say, and what you must never do.

Language: reply to the user in their language; keep technical identifiers (paths, flags) as in the scripts.


Your job in one sentence

Use scripts/pack_openclaw.py and scripts/apply_openclaw.py from this skill to export or restore workspace data (and optional layers only if the user clearly opts in after you warn them). You own preview, collision handling, and consent—the scripts only write files by path.


When the user asks to export (pack)

  1. Run pip install -r requirements.txt if dependencies may be missing.
  2. Run python scripts/pack_openclaw.py --dry-run with the same flags you plan for the real pack; show the user what paths would be included.
  3. Explain: default pack is workspace/ only. List optional layers (--managed-skills, session flags, config snapshot flags) and do not add any until the user separately approves each, after you give the short risk line (size, transcripts, secrets)—see Before any real disk write.
  4. Run the real pack: python scripts/pack_openclaw.py with only approved flags.
  5. Give the user the zip path. Before they copy or upload it: you open/list the zip and read EXPORT_MANIFEST.txt; confirm it matches what you promised (paths + layers).

When the user asks to import (apply)

  1. If the zip is not clearly from a trusted source or from this skill’s pack layout (workspace/, EXPORT_MANIFEST.txt, …), stop and say why you will not apply it without their confirmation.
  2. Run pip install -r requirements.txt if needed.
  3. Tell the user to back up $OPENCLAW_HOME (or %USERPROFILE%\.openclaw) and the target workspace—or apply to a throwaway copy—unless they explicitly accept overwrite risk after you state it once.
  4. You read EXPORT_MANIFEST.txt inside the zip, then run
    python scripts/apply_openclaw.py --zip <path> --dry-run
    with --openclaw-home, --workspace, and --config as the environment needs. Treat the combined manifest + dry-run output as the write contract.
  5. Walk the user through which paths would be created/overwritten. For overlaps on memory / persona / skills, follow Merge and conflicts (your work; not in scripts)do not run non–dry-run apply on a live workspace until conflicts are resolved or the user explicitly chooses full replace for that subtree.
  6. Add --apply-managed-skills, session flags, or --apply-config only after separate approval and the warnings in Before any real disk write.
  7. Run apply without --dry-run only when the above is satisfied. If config was restored, remind: they still need valid auth on this machine; old paths inside openclaw.json may be wrong here.
  8. Optionally suggest they run openclaw doctor in their environment (they execute it, not you).

Before any real disk write (you follow this order)

Skip a step only if the user opts out after you repeat the concrete risk.

  1. Dry-run first — pack and apply both support --dry-run. The printed paths are what a real run would touch.
  2. Read EXPORT_MANIFEST.txt in the zip — authoritative list of packed paths; pair with apply dry-run to see destination collisions.
  3. Backups — dry-run does not change disk; it is not a backup. For apply, insist on backup or throwaway target unless they waive.
  4. Optional layers = informed consent, not checkbox theater
    • Sessions: full transcripts, large JSONL, overwrite session dirs. Do not pass pack/apply session flags unless the user understands that.
    • Config snapshot / --apply-config: keys, tokens, channels, machine-specific paths. Do not enable without that acknowledgment.
  5. Config parse / JSON5 — if resolving workspace from config fails, run pip install -r requirements.txt (includes json5) or pass --workspace explicitly.

What the scripts actually do (so you do not mislead)

  • Pack and apply are filesystem steps: extract or copy bytes to paths. No semantic merge, no three-way merge, no conflict UI in Python.
  • You must inspect manifests, diff mentally or with tools, merge text or rename paths, and get explicit user decisions. Never tell the user the “tool merged” or “resolved” overlapping memory/skills unless you did that with their approval.

If you follow previews + consent + collision handling, you can honestly say the flow is transparent; if you skip that, you risk silent data loss.


Safety: what you must assume and say

  • Assume the archive may hold sensitive material: persona, MEMORY.md, logs, workspace skills; with optional layers, session JSONL and openclaw.json (secrets, channels).
  • Do not pack or encourage packing ~/.openclaw/credentials/. Apply never writes credentials; tell the user they must re-login / re-pair on a new machine unless they consciously accept copying secrets (you still do not pack credentials via these scripts).
  • Warn against putting the zip on untrusted or public storage.
  • Overwrite rule: same path ⇒ destination file replaced. Same path ≠ same meaning. Only openclaw.json gets a .bak.<timestamp> when using --apply-config; other paths are not auto-backed up.

Merge and conflicts (your work; not in scripts)

  • A path is an address, not proof two files are equivalent. Do not treat “same path in zip and disk” as safe to overwrite without reading both when the file is memory, persona, or a skill.
  • Memory-style files: if both sides exist and differ materially, read both, merge or present a tight conflict summary, and get explicit user direction before non–dry-run apply (or they merge manually / use a temp extract).
  • Skills (SKILL.md etc.): divergent purpose or triggers ⇒ do not pick a winner alone; offer keep local / take zip / merge / rename path so both can exist.
  • Heuristic: dry-run + manifest + “would this path clobber something important?” ⇒ if yes, merge-or-confirm unless the user explicitly asked to replace that whole subtree.

Pack: default vs optional

ContentPath inside zipIn default pack?
Workspace (persona, memory, workspace skills, canvas, etc.)workspace/yes
Managed skillsmanaged-skills/no — --managed-skills
Sessionssessions/<agentId>/sessions/no — session flags + acknowledgement; large, sensitive, full transcripts
Config snapshotconfig/openclaw.jsonno — config flags + acknowledgement; secrets, machine paths
Credentialsn/anever

Apply: default vs optional

Match flags to what is in the zip. If a layer is in the zip but flags are missing, the script warns and skips that layer.

ContentActionDefault apply?
WorkspaceExtract workspace/* → target workspaceyes, unless --no-apply-workspace
Managed skills<openclaw-home>/skills/no — --apply-managed-skills
Sessions<openclaw-home>/agents/<id>/sessions/no — --apply-sessions + --i-know-restoring-sessions-overwrites
Config<openclaw-home>/openclaw.json (existing → .bak.<timestamp>)no — --apply-config + --i-know-config-overwrites-secrets

Paths (how you resolve them)

  • OpenClaw home: $OPENCLAW_HOME or ~/.openclaw; Windows: %USERPROFILE%\.openclaw.
  • Pack: if --workspace omitted, script reads config. Apply: --workspace may create the dir; if omitted, config must parse. On a fresh machine, prefer openclaw onboard or pass --workspace explicitly.
  • Run pack and apply in the same environment family (e.g. both WSL) so paths mean the same thing.

Examples (you adapt paths for the user’s OS)

Workspace-only apply, dry-run then real:

python scripts/apply_openclaw.py --zip ./openclaw-user-export-xxx.zip \
  --openclaw-home ~/.openclaw \
  --workspace ~/.openclaw/workspace \
  --dry-run
python scripts/apply_openclaw.py --zip ./openclaw-user-export-xxx.zip \
  --openclaw-home ~/.openclaw \
  --workspace ~/.openclaw/workspace

All optional apply layers — only after the user approved each flag’s risk:

python scripts/apply_openclaw.py --zip ./export.zip \
  --openclaw-home ~/.openclaw --workspace ~/.openclaw/workspace \
  --apply-managed-skills \
  --apply-sessions --i-know-restoring-sessions-overwrites \
  --apply-config --i-know-config-overwrites-secrets

CLI reference (copy-paste skeletons)

Pack:

python scripts/pack_openclaw.py [--workspace PATH] [--openclaw-home PATH] [--config PATH]
  [-o FILE.zip] [--exclude-git | --no-exclude-git] [--managed-skills]
  [--sessions --i-know-sessions-are-large-and-sensitive]
  [--config-snapshot --i-know-config-may-contain-secrets]
  [--dry-run] [--manifest-sha256] [--sha256-max-mb N]

Apply:

python scripts/apply_openclaw.py --zip FILE.zip [--openclaw-home PATH] [--workspace PATH] [--config PATH]
  [--no-apply-workspace] [--apply-managed-skills]
  [--apply-sessions --i-know-restoring-sessions-overwrites]
  [--apply-config --i-know-config-overwrites-secrets]
  [--dry-run]

When to activate this skill (trigger hints)

IntentExample user phrases
Exportbackup workspace, export memory, pack openclaw
Importnew PC restore, import zip, apply backup, restore openclaw
Chinese一键打包, 一键应用, 导入 zip, 迁移

Quick commands (you run from skill root)

GoalCommand
Pack previewpython scripts/pack_openclaw.py --dry-run
Packpython scripts/pack_openclaw.py
Apply previewpython scripts/apply_openclaw.py --zip x.zip --dry-run
Applypython scripts/apply_openclaw.py --zip x.zip
Dependenciespip install -r requirements.txt

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