AB finding-healthcare-practices-via-google-search
Finds medical practices, clinics, dental offices, and healthcare providers via Google Search using apidojo's Google Search Scraper on Apify. Triggers when the user asks to: find medical practices for outreach, discover dental offices or clinics via Google, build a list of healthcare providers in a specific city, find doctors or medical groups for vendor sales, prospect healthcare practices for software or supply sales, identify hospitals or urgent care centers by location, or compile a healthcare provider list from Google results. Returns practice name, website URL, and Google snippet per result. Ideal for HealthTech SaaS vendors, medical suppliers, and B2B service companies targeting healthcare practices.
Finds medical practices, clinics, dental offices, and healthcare providers via Google Search using apidojo's Google Search Scraper on Apify.
As a process B 65/100 · Nearly there — weak spots: result and completion, 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 65/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 762 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
- +2Single-language instructions
- +3Description length 715: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.