unfairgaps

unfairgaps is a Market & industry research skill for AI agents, published by AyanbekDos in the unfairgaps-os repository on GitHub. Skillspace rates unfairgaps C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Find documented UNFAIRGAPS - systemic regulatory holes where a product can plug the leak - using court filings, regulatory fines, and enforcement data. Five operations in one methodology - industry-scan, validate-idea, site-audit, customer-pains, profession-scan. Dual mode - native Claude Code (WebSearch+WebFetch) or delegates to run.py if PERPLEXITY_API_KEY is set. profession-scan is native-only and country-aware (any country).

Grade
C
Quality
74 / 100
Safety
Passed
GitHub stars
110

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.

View source on GitHubAyanbekDos/unfairgaps-os

Our review

Architecture
88 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
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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