AB google-ai-search-optimization
Audit websites, pages, content plans, or SEO recommendations for Google Search generative AI features such as AI Overviews and AI Mode. Use whenever the user asks about AI SEO, AEO, GEO, Google AI Overviews visibility, AI Mode readiness, agent-friendly site optimization, or whether tactics like llms.txt, chunking, structured data, or AI-generated content help Google generative search.
As a process B 78/100 · 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: 3. 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 78/100
- 0Progress reporting. Says nothing while it works
- 30Inputs and preconditions. Does not say what the process needs to start
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Failures and branches. 4 branches
- 100Tools and files. No external tools needed
- 100Steps. 43 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1081 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 387: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 43 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.