BB apple-swift-mcp
This skill should be used when the user asks about Apple app data via the native Swift MCP — Calendar, Reminders, Contacts, Maps, Mail, Messages, Notes, Photos, or Apple Music playlists on macOS. Triggers on phrases like "check my calendar", "find contact", "send iMessage", "search my notes", "recent emails", "find photos of", "make a playlist", "add this song to my playlist", "sort my playlist", or any macOS-native app automation. Requires macOS 14+ on Apple Silicon; faster than the AppleScript-backed Node variant.
This skill should be used when the user asks about Apple app data via the native Swift MCP — Calendar, Reminders, Contacts, Maps, Mail, Messages, Notes…
As a process B 73/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- 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: 2. 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 73/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Inputs and preconditions. Does not say what the process needs to start
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 35 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2640 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +3Description length 521: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 35 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.