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BD clawback

Backup and restore your OpenClaw workspace to GitHub

ClawHub Agent Skills author: nickconstantinou v1.0.6 13 files · 3 scripts body ≈ 1 154 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceGitHubInfrastructuretype 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
B
80/100
safety, quality, tests
Safety 60%
91
Quality 40%
64
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: clawback (ClawHub)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Broad scope meta-agent-memory-dump HEARTBEAT.md
    Agent memory / workspace files bundled with the skill (4) — likely a workspace dump with personal data or tokens
    HEARTBEAT.md, IDENTITY.md, SOUL.md, USER.md
  • low Exfiltration read-dotenv README.md:9
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv SKILL.md:83
    Reads a .env file
    cp .env.example .env
  • low Secrets in code secret-github-token SKILL.md:143
    GitHub token (placeholder value)
    echo "My API key is ghp_…xyz" > /tmp/test-workspace/AGENTS.md
    placeholder
  • low Secrets in code secret-labelled-token SKILL.md:163
    Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)
    echo "Real API key: sk-r…890" > /tmp/test-workspace/AGENTS.md
    placeholder

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 44/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (clawback) differs from the folder (clawsync)
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 36 steps
  • 100Execution cost. Instruction body is 1154 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 52: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
The skill appears to be a legitimate GitHub backup and restore tool, but it includes under-scoped autonomous actions and credential persistence risks that users should review before installing.
LLM: suspicious (medium) · VirusTotal: benign · 28 May 2026