AC afrexai-sales-funnel-engine
Design, build, optimize, and scale sales funnels for any business model. Use when mapping customer journeys, diagnosing conversion leaks, building landing pages, designing email sequences, setting up attribution, A/B testing funnel stages, or scaling paid acquisition. Covers B2B, B2C, SaaS, services, ecommerce, and hybrid funnels. Trigger on: sales funnel, conversion funnel, funnel optimization, lead funnel, why aren't people buying, funnel audit, landing page, email sequence, conversion rate, customer journey, pipeline conversion, funnel metrics.
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7528 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 10 mutating operations with no state check
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 7528 tokens
- 100Tools and files. No external tools needed
- 100Steps. 72 steps
- 100Consistency. Name and required fields are in place
- low 11 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 553: enough signal without eating the budget
- +4Structure: 46 headings
- +3Step-by-step instructions: 72 items
- +4Has examples (20 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.