AB schema-markup
When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data," "schema validation error," "Schema Markup Validator," "Google Rich Results Test," "FAQ schema," "Article schema," "Organization schema," "JobPosting," "HowTo," "Event," "SoftwareApplication," "BreadcrumbList," "WebSite," "Recipe," "Product," or "Dataset." For SERP feature types and zero-click patterns, use serp-features. For AI search visibility strategy (not markup), use generative-engine-optimization.
As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, consistency, 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 72/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (schema-markup) differs from the folder (schema-markup-seo)
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 4 branches
- 70Execution cost. Instruction body is 4783 tokens
- 100Tools and files. No external tools needed
- 100Steps. 31 steps
- 100When it triggers. States when to use and when not to
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 24 example trigger phrases
- +3Description length 689: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 31 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.