BB date-night
Your AI date night concierge — plans, books, and coordinates an entire evening out through browser automation. Say "plan a date night" and it handles everything: restaurant reservations (OpenTable, Resy), movie tickets (Fandango, Megaplex, AMC), event tickets with price comparison (SeatGeek, Ticketmaster, StubHub), weather checks, drive-time estimates, budget totals, calendar events, and partner notifications. Configurable dietary preferences, childcare reminders, favorite theaters, and babysitter-rate budgeting. First run walks through a friendly onboarding — after that, just tell it what kind of night you want. Triggers: date night, dinner reservation, book a table, OpenTable, Resy, find restaurants, movie tickets, what's playing, concert tickets, sports tickets, events near me, dinner and a movie, plan a date, date ideas, cancel reservation, modify reservation, reconfigure date night preferences.
As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 66/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, write, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 29 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3952 tokens
- 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
- low 12 top-level sections: this looks like several domains in one skill
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 912: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 28 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (15 code blocks)
- +4Reference files are cited in the instructions (12 of 12)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.