asset-scraping
asset-scraping is a Web scraping & data collection skill for AI agents, published by deanwhitex in the AIW2.0STACK repository on GitHub. Skillspace rates asset-scraping D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Use during Stage 4 (asset scraper) of the website factory pipeline to autonomously harvest the client's brand assets, logo, trust badges, project photos, owner/team photos, and any niche-specific asset categories, from their website, Google Business Profile, and linked social channels into the client Assets folder. Halts the entire pipeline if no logo is found. Uses tools/apify-scrape.py for reliable scraping; falls back to native WebFetch only on Apify failure. Never fabricates assets, only flags missing ones.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 46
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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