AB newsletter-growth-ops
Use when the user asks to grow newsletter subscribers, evaluate acquisition channels, convert social followers to email, re-engage inactive readers, analyze signup sources, design welcome surveys, or plan growth experiments. For audience proof use newsletter-audience-intelligence; for sponsor pipelines use newsletter-sponsor-ops; for monetization model selection use newsletter-monetization-strategy; for ROI, costs, or upgrade decisions use newsletter-roi-dashboard.
Use when the user asks to grow newsletter subscribers, evaluate acquisition channels, convert social followers to email, re-engage inactive readers, analyze…
As a process B 76/100 · Nearly there — weak spots: failures and branches, 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 76/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 608 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 469: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 24 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.