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DF lulu-monitor

AI-powered LuLu Firewall companion for macOS. Monitors firewall alerts, analyzes connections with AI, sends Telegram notifications with Allow/Block buttons. Use when setting up LuLu integration, handling firewall callbacks, or troubleshooting LuLu Monitor issues.

Not recommendedcritical or high security findings · low grade D
modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files · 4 scripts body ≈ 1 113 tokens Open the sourcegithub.com↗ analyzed 3 d ago

AI-powered LuLu Firewall companion for macOS.

As a process F 48/100 · Will not run — References files that are not bundled: screenshot.png

IntegrationTelegramSoftware developmentWriting and documentstype 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
D
59/100
safety, quality, tests
Safety 60%
49
Quality 40%
73
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: screenshot.png
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
0
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.
  2. The text references files that are not there: add them or drop the references.
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

  • high Dangerous commands cmd-persistence scripts/configure.sh:40
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$HOME/Library/LaunchAgents/com.openclaw.lulu-monitor.plist"
  • high Dangerous commands cmd-persistence scripts/install.sh:80
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$LAUNCH_AGENTS/$PLIST_NAME"
Medium and low: 3
  • medium Dangerous commands cmd-persistence scripts/configure.sh:39
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    launchctl unload "$HOME/Library/LaunchAgents/com.openclaw.lulu-monitor.plist" 2>/dev/null || true
    code literal
  • medium Dangerous commands cmd-persistence SKILL.md:140
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (documentation of a security skill)
    launchctl unload ~/Library/LaunchAgents/com.openclaw.lulu-monitor.plist
    security skill
  • medium Dangerous commands cmd-persistence SKILL.md:141
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (documentation of a security skill)
    launchctl load ~/Library/LaunchAgents/com.openclaw.lulu-monitor.plist
    security skill

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: screenshot.png

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: screenshot.png
  • 0Tools and files. 1 referenced file(s) missing: screenshot.png
  • 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
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1113 tokens
  • 100Running it twice. Mutating operations check current state

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
  • -2localhost URLs: will not work for another user
  • -31 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.