AB finding-freelancers-by-skill-on-twitter
Finds freelancers and independent contractors to recruit using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: find freelancers on Twitter for contract work, discover independent contractors for hire in a skill area on X, find freelance developers designers writers or marketers on Twitter, identify consultants or solopreneurs by specialty on Twitter for project work, find contractors available for hire via social signals, build a freelancer roster from Twitter for agency or project needs, or find independent workers actively seeking clients. Returns handle, name, skill set (from bio), client signals, follower count, and availability indicators. Ideal for agencies, startup operators, and project managers needing on-demand specialist talent.
Finds freelancers and independent contractors 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 · 2
✓ No critical or high findings
Medium and low: 2
-
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=…" \
placeholder -
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=…" \
placeholder
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 1304 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 770: 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.