AB waiting-list
Design and build waiting-list portals for anticipated goods or services: classify whether the experience needs interest capture, verified early access, referral growth, a virtual waiting room, appointment backfill, or scarce-item allocation; choose a reversible architecture; and define the state machine, abuse controls, consent and email lifecycle, fairness, observability, and release gates. Optionally validate supplied email and phone contacts with expiring magic links or provider-managed verification, then feed eligible, consented records to a runtime-configured CRM adapter. Use for prelaunch signups, beta access, launches, bookings, reservations, traffic-spike queues, and premium or cinematic campaign experiences. Do not use for generic landing-page copy, ordinary CRM or email operations, or checkout and inventory systems in isolation; route those parts to the appropriate specialist skill.
Design and build waiting-list portals for anticipated goods or services: classify whether the experience needs interest capture, verified early access…
As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, progress reporting
How to improve
- 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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 65/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 4433 tokens
- 85Steps. 34 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- high The skill tells the model to perform an irreversible action with no human approval
- low No test case covers injection arriving through data
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
- +3Description length 905: 120–800 characters recommended
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +4Structure: 14 headings
- +3Step-by-step instructions: 34 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (8 of 9)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.