AB finding-data-scientists-on-twitter
Finds data scientists and ML engineers to recruit using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: find data scientists on Twitter for recruiting, discover machine learning engineers or AI researchers to hire from X, find data analysts or ML practitioners by specialization on Twitter, identify NLP computer vision or LLM engineers via social signals, find data science professionals open to work on Twitter, build a data science talent pipeline from social, or find researchers posting about job opportunities. Returns handle, name, ML specialty (from bio/tweets), stack (Python/R/TensorFlow), follower count, and open-to-work signals. Ideal for ML engineering hiring managers, AI research labs, and data-driven startups.
Finds data scientists and ML engineers to recruit using apidojo's Twitter scrapers on Apify.
As a process B 78/100 · 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 · 4
✓ No critical or high findings
Medium and low: 4
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low Exfiltration
exfil-secret-in-urlskill-card.md:41Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)- [Apify Twitter user scraper actor](https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=…)
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low Exfiltration
exfil-secret-in-urlskill-card.md:42Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)- [Apify tweet scraper actor](https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=…)
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low Exfiltration
exfil-secret-in-urlSKILL.md:88Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)"https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=…" \
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low Exfiltration
exfil-secret-in-urlSKILL.md:107Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=…" \
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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 78/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1297 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 748: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 6 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.