AC airpoint
Control a Mac through natural language — open apps, click buttons, read the screen, type text, manage windows, and automate multi-step tasks via Airpoint's AI computer-use agent.
As a process C 56/100 · Has gaps — weak spots: result and completion, consistency, running it twice
This is a copy of a skill from another catalog; the rating counts the canonical one: airpoint (ClawHub)
How to improve
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 · 0
✓ No critical or high findings
Files scanned: 3. 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 56/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (airpoint) differs from the folder (airpoint-1-3-16)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 23 steps
- 100Execution cost. Instruction body is 1452 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 178: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.
External checks
ClawHub: suspicious
This skill is transparent about giving an AI tool broad control of a Mac, but that level of screen access and autonomous action needs careful review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026