BB apify-tiktok-scraper
Research TikTok videos, profiles, hashtags, comments and followers with engagement statistics through the harshmaur/tiktok-scraper Apify Actor. No TikTok login.
Promises to scrape TikTok via Apify Actor—videos, profiles, hashtags, comments, followers with metrics. No login required. Two files, 2496 tokens, no critical errors. Scores: quality 80, process 69—the gap hints at architectural or documentation issues. Never ran on models, sandbox untested. Works on Claude and Hermes.
Grade B means "acceptable but flawed." The skill works for basic data collection if the Apify Actor stays alive and unbanned. Install if you're comfortable with TikTok potentially cutting access tomorrow and the quality score feels sufficient for your use case.
Research TikTok videos, profiles, hashtags, comments and followers with engagement statistics through the harshmaur/tiktok-scraper Apify Actor.
As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice
The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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
- warning
description-long-hermesdescription is 160 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "risk" - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "source_repo" - note
frontmatter-keyunknown frontmatter key "source_type" - note
frontmatter-keyunknown frontmatter key "date_added" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "license_source"
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 9 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2776 tokens
- 100Progress reporting. Reports progress
- high The skill tells the model to perform an irreversible action with no human approval
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 160: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 30 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.