BC mac-cleaner
Replace CleanMyMac, DaisyDisk, and similar paid Mac cleanup apps — for free. Mac Cleaner is an automated weekly macOS disk cleanup agent that runs silently in the background, freeing gigabytes every week without any subscription, API key, or external service. Cleans ~/Library/Caches, old logs, Trash, npm/Homebrew cache, and stale build artifacts. Installs a Mission Control dashboard and a Sunday 3 AM cron job on first run. Trigger when: "clean my mac", "disk cleanup", "free up disk space", "mac cleaner", "clean disk", "weekly cleanup", "I'm running out of space", "install mac cleaner".
As a process C 61/100 · Has gaps — weak spots: result and completion, consistency, execution cost
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.
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.
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
- 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
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high Dangerous commands
cmd-persistenceSKILL.md:1175Persistence mechanism (cron / launchd / scheduled task / autorun registry)launchctl unload ~/Library/LaunchAgents/ai.openclaw.mission-control.plist 2>/dev/null; pkill -f "next.*mission-control" 2>/dev/null; sleep 1; kill -9 $(pgrep -f "next.*mission-control") 2>/dev/null; r
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 10325 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (mac-cleaner) differs from the folder (macos-mac-cleaner)
- 40Execution cost. Instruction body is 10325 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, node) 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
- 70Failures and branches. 10 branches
- 100Steps. 11 steps
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 592: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 11 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.