AA building-twitter-industry-watchlist
Builds a curated Twitter industry watchlist of key voices using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: build a Twitter watchlist for an industry, find key Twitter accounts to follow in a niche, create a curated list of thought leaders in a sector on X, identify the most influential Twitter accounts in a business category, build a Twitter list for industry monitoring, find the signal-to-noise accounts in a topic area, or compile the must-follow accounts for staying current in an industry. Returns account list with handle, follower count, engagement rate, topic focus, and influence score. Ideal for business analysts, investors, executives, and professionals doing industry intelligence.
Builds a curated Twitter industry watchlist of key voices using apidojo's Twitter scrapers on Apify.
As a process A 81/100 · Runs to the end — weak spots: 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
exfil-secret-in-urlSKILL.md:91Credential 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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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 81/100
- 0Progress reporting. Says nothing while it works
- 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. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1075 tokens
- 100Running it twice. No mutating operations
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 722: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 10 items
- +3Output format is stated explicitly
- +4Has examples (6 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.