AC creator-scraper-cv
Creativault creator data collection and outreach skill. Search and collect creator/influencer data from TikTok, YouTube, Instagram, and Twitter. Send outreach emails to discovered creators with automatic conversation management, batch sending, and follow-up tracking. Supports multi-dimensional search, similar/lookalike creator discovery, batch collection by links/usernames/keywords, task tracking, data export (xlsx/csv/html), and email outreach (single/batch send, templates, smart timing, metrics). Use when: creator search, influencer scraping, KOL search, KOL analytics, social media data extraction, TikTok scraper, YouTube scraper, Instagram scraper, Twitter scraper, influencer discovery, similar creators, lookalike, outreach, email outreach, send email to creator, batch email, follow-up, 达人采集, KOL 搜索, 网红数据, 达人分析, 达人搜索, 相似达人, 社交媒体数据, 建联, 发邮件, 批量发送.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
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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medium Exfiltration
net-redirectable-api-keyscripts/_api_client.mjs:12Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 30. 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 51/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (creator-scraper-cv) differs from the folder (cv-creator-scraper)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 20 steps
- 100Execution cost. Instruction body is 967 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)
- +3Description length 861: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -316 of 18 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 8 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.