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good-measure-giving
good-measure-giving에는 uabbasi에서 수집한 skills 10개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
Islamic jurisprudence expertise on zakat - the 8 categories of recipients (asnaf), scholarly interpretations across madhabs, and how to assess charity alignment with zakat eligibility. Activates when working on zakat classification, wallet tags, or donor guidance.
Unified analytics (Cloudflare + Firestore + GA4). Pull traffic data, user activity, feature adoption, and giving metrics. Use when checking site performance, user behavior, or feature usage.
Write accessible, research-backed white papers and guides on complex topics. Target 8th grade readability while citing best-in-class scholarship. Output is 2-5 page PDFs that compete for attention in a TikTok world. NOT for charity narratives.
Run the charity evaluation pipeline - extraction, 4-stage V2 workflow, Supabase patterns, versioning. Use when working on collectors, scrapers, pipeline code, database queries, or debugging data flow.
Philanthropic expertise on charity evaluation methodologies, grantmaking best practices, cost-effectiveness analysis, and strategic giving. Activates when working on charity scoring, evaluation frameworks, donor guidance, or impact assessment.
Deep expertise on IRS Form 990 structure, fields, and nonprofit financial analysis. Activates when working on Form 990 parsing, ProPublica API integration, or charity financial evaluation code.
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
Expert guidance on LLM prompting patterns used in this project. Covers versioned prompts, schema enforcement, category calibration, multi-provider fallback, and narrative generation. Activates when working on prompts, LLM integration, or evaluation logic.
Test web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing screenshots, and viewing browser logs. Use when testing the website or debugging UI issues.