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Cloud knowledge backup and retrieval using Supermemory.ai free tier. Store high-value insights to the cloud and search them back when local memory is insufficient. Uses standard /v3/documents and /v3/search endpoints (no Pro-only features).

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Broedkrummen v1.0.0 8 files · 1 script body ≈ 1 279 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ReferenceInfrastructuretype 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
73/100
safety, quality, tests
Safety 60%
66
Quality 40%
84
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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.

Dangerous commands
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 · 9

  • high Dangerous commands cmd-persistence install_cron.sh:63
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "$CRON_CMD") | crontab -
Medium and low: 8
  • medium Dangerous commands cmd-persistence install_cron.sh:60
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)
    crontab -l 2>/dev/null | grep -v "$CRON_MARKER" | crontab - || true
    detector
  • medium Dangerous commands cmd-persistence install_cron.sh:79
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)
    crontab -l 2>/dev/null | grep -v "$CRON_MARKER" | crontab -
    detector
  • low Exfiltration read-dotenv install_cron.sh:18
    Reads a .env file (detector / deny-list definition)
    CRON_CMD="$CRON_SCHEDULE cd $WORKSPACE_DIR && source .env && $PYTHON $SKILL_DIR/auto_capture.py --days 3 >> $LOG_FILE 2>&1 # $CRON_MARKER"
    detector
  • low Dangerous commands cmd-cron-mention install_cron.sh:60
    Mentions editing / listing crontab
    crontab -l 2>/dev/null | grep -v "$CRON_MARKER" | crontab - || true
  • low Dangerous commands cmd-cron-mention install_cron.sh:63
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "$CRON_CMD") | crontab -
  • low Dangerous commands cmd-cron-mention install_cron.sh:70
    Mentions editing / listing crontab (detector / deny-list definition; string literal in code, not executed)
    echo "Verify with: crontab -l | grep $CRON_MARKER"
    detectorcode literal
  • low Dangerous commands cmd-cron-mention install_cron.sh:78
    Mentions editing / listing crontab
    if crontab -l 2>/dev/null | grep -q "$CRON_MARKER"; then
  • low Dangerous commands cmd-cron-mention install_cron.sh:79
    Mentions editing / listing crontab
    crontab -l 2>/dev/null | grep -v "$CRON_MARKER" | crontab -

Files scanned: 8. 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 61/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 14 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1279 tokens

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 240: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

External checks

ClawHub: suspicious
This skill does what it says, but it can automatically upload local session-memory content to Supermemory.ai and persist that behavior with cron, so users should review it carefully before installing.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026