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CC snapshot

Backup and restore the .openclaw agent folder — encrypted snapshots pushed to a private GitHub repo. Use this skill whenever the user mentions backup, restore, snapshot, save state, migrate workspace, move to a new machine, or any request to preserve or recover the .openclaw agent. Also trigger when the user asks about available backup versions, wants to check backup status, or needs to set up the backup system on a new workspace. Even casual phrasing like "save my agent" or "load my stuff on the new box" should trigger this skill.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: KrishBhimani v1.2.0 MIT-0 7 files · 4 scripts body ≈ 1 168 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Backup and restore the .openclaw agent folder — encrypted snapshots pushed to a private GitHub repo. Use this skill whenever the user mentions backup…

As a process C 60/100 · Has gaps — weak spots: result and completion, failures and branches

ProcedureGitHubAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
76
Quality 40%
86
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Tools and files w 18
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

  • high Exfiltration intent-browser-credential-store skill-card.md:31
    Accesses a browser credential / cookie store
    Mitigation: Confirm the intended backup version and current local state before running restore, and treat restore as a potentially destructive operation.
Medium and low: 2
  • medium Dangerous commands cmd-autorun-instruction SKILL.md:114
    Instructs the agent to auto-run a script on every session
    **Always run setup.py before backup or restore.** It's idempotent (safe to run every time) and ensures GPG is installed, the transport repo exists, and the local repo is synced with GitHub. This preve
  • low Exfiltration read-dotenv env-example.txt:3
    Reads a .env file (test fixture / example file)
    #   cp .env.example .env
    fixture

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 29 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1168 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (11 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -31 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 537: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

External checks

ClawHub: suspicious
This backup skill is mostly purpose-aligned, but it has unsafe backup, restore, credential, and setup behavior that could expose or delete local data if used as written.
LLM: suspicious (high) · VirusTotal: · 14 Sept 2026