AB tracking-youtube-trending-topics-by-niche
Tracks trending YouTube topics and video formats in a specific niche using apidojo's YouTube scraper on Apify. Triggers when the user asks to: find trending YouTube topics in a niche, discover what videos are getting views right now in a category, identify trending YouTube formats or themes in an industry, find high-performing YouTube video ideas from search trends, research what the YouTube algorithm is currently rewarding in a topic area, discover rising YouTube creators in a niche, or analyze what video angles perform best on YouTube in a category. Returns trending video titles, view counts, engagement metrics, format patterns, and topic themes. Ideal for YouTube content creators, video marketers, and brand video strategists.
Tracks trending YouTube topics and video formats in a specific niche using apidojo's YouTube scraper on Apify.
As a process B 75/100 · Nearly there — weak spots: running it twice, 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 · 2
✓ No critical or high findings
Medium and low: 2
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low Exfiltration
exfil-secret-in-urlSKILL.md:94Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)curl -X POST "https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=…" -H "Content-Type: application/json" -d '{"searchKeywords": ["personal finance tips", "best investingplaceholder -
low Exfiltration
net-credential-useSKILL.md:94Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)curl -X POST "https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=…" -H "Content-Type: application/json" -d '{"searchKeywords": ["personal finance tips", "best investingvendor-host
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 75/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 5 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1352 tokens
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)
- +2Single-language instructions
- +3Description length 738: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 5 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.