AB scraping-instagram-comments
Extracts comments from Instagram posts using apidojo's Instagram Comments Scraper on Apify. Triggers when the user asks to: get all comments on an Instagram post, scrape Instagram comment data, export comments from an Instagram URL, fetch comment text and engagement from Instagram posts, collect commenter usernames from a post, or download audience reaction data from Instagram content. Returns comment text, like count, reply count, commenter username, verified status, and timestamp. Ideal for sentiment analysts, community managers, and social media researchers.
Extracts comments from Instagram posts using apidojo's Instagram Comments Scraper on Apify.
As a process B 71/100 · 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 · 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 71/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 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
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 669 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 567: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 5 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.