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CD Janitor - AI Agent Cleanup & Session Management Skill

Think of Janitor as your AI Agent's Intelligent Maintenance Crew that:

modbender/skill-library-mcp Agent Skills author: modbender MIT 24 files · 2 scripts body ≈ 2 638 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Think of Janitor as your AI Agent's Intelligent Maintenance Crew that:

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubAI and agentsData and analyticstype 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
67/100
safety, quality, tests
Safety 60%
74
Quality 40%
57
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

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

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. 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 · 10

✓ No critical or high findings

Medium and low: 10
  • medium Dangerous commands cmd-privilege README.md:473
    Privilege escalation / world-writable permissions
    sudo cp systemd/janitor-monitor.service.template /etc/systemd/system/janitor-monitor@.service
  • medium Dangerous commands cmd-privilege systemd/README.md:135
    Privilege escalation / world-writable permissions
    sudo cp /etc/systemd/system/openclaw.service /etc/systemd/system/openclaw.service.backup
  • medium Dangerous commands cmd-privilege systemd/README.md:187
    Privilege escalation / world-writable permissions
    sudo rm /etc/systemd/system/janitor-monitor@.service
  • medium Dangerous commands cmd-privilege systemd/README.md:188
    Privilege escalation / world-writable permissions
    sudo rm /etc/systemd/system/openclaw@.service
  • low Dangerous commands cmd-background-process install.sh:155
    Starts a background / autostarted process (string literal in code, not executed)
    echo "   sudo systemctl enable janitor-monitor@$USER"
    code literal
  • low Dangerous commands cmd-background-process README.md:475
    Starts a background / autostarted process
    sudo systemctl enable janitor-monitor@$USER
  • low Exfiltration exfil-webhook-url src/services/notifier.js:178
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    const url = `https://api.telegram.org/bot${this.config.telegram.botToken}/sendMessage`;
    placeholder
  • low Dangerous commands cmd-background-process systemd/README.md:119
    Starts a background / autostarted process
    sudo systemctl enable janitor-monitor@$USER
  • low Dangerous commands cmd-background-process systemd/README.md:145
    Starts a background / autostarted process
    sudo systemctl enable openclaw@$USER
  • low Dangerous commands cmd-cron-mention systemd/README.md:271
    Mentions editing / listing crontab
    crontab -e

Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (Janitor - AI Agent Cleanup & Session Management Skill) differs from the folder (janitor)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, git, node) that frontmatter does not declare
  • 85Steps. 33 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 2638 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 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

  • +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 70: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 45 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (24 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.