AB finding-hospitality-brands-on-instagram
Discovers hotels, travel brands, resorts, and hospitality businesses on Instagram using apidojo's Instagram Scraper on Apify. Triggers when the user asks to: find hotels on Instagram for B2B outreach, discover travel brands or resorts active on social media, build a list of hospitality businesses on Instagram, find boutique hotels or tour operators via Instagram, prospect hotel and resort brands for software or vendor sales, or identify travel companies active on Instagram. Returns account handle, follower count, bio, engagement data per post. Ideal for hospitality SaaS vendors, travel tech providers, and B2B service companies targeting hotels.
Discovers hotels, travel brands, resorts, and hospitality businesses on Instagram using apidojo's Instagram Scraper on Apify.
As a process B 72/100 · 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 72/100
- 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
- 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. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 684 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 652: 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.