AC peak-end-rule
Activate when: user says 'how will they remember this,' 'experience design,' 'journey design,' 'memorable moment,' 'end-of-experience,' or 'our NPS is lower than expected'; when designing or auditing a multi-stage customer or user journey; when a competitor with similar quality earns higher recommendation rates. Do NOT activate when: the interaction is instantaneous with no temporal sequence (single API call, one-tap action); or when total real-time utility matters more than retrospective memory (welfare assessments, health measurements). More: deciqai.com/c/peak-end-rule
Activate when: user says 'how will they remember this,' 'experience design,' 'journey design,' 'memorable moment,' 'end-of-experience,' or 'our NPS is lower…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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: 4. 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 59/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 40 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2266 tokens
- 100Running it twice. No mutating operations
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 578: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 40 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.