원클릭으로
structured-coding-with-ai
structured-coding-with-ai에는 Open-Paws에서 수집한 skills 16개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
GitHub workflow for AI-assisted advocacy development — issue-first, worktree-per-task, plan→review→implement loops, desloppify gate, post-PR monitoring
General-purpose subagent delegated by /run. Runs pipeline orchestration algorithm: discover pipeline items, identify stage, dispatch per-stage subagents via Task, classify outcomes, write report.
Security audit workflow for advocacy projects — dependency verification, zero-retention compliance, slopsquatting defense, encrypted storage, instruction file integrity, device seizure readiness, ag-gag exposure assessment
Security audit workflow for advocacy projects — dependency verification, zero-retention compliance, slopsquatting defense, encrypted storage, instruction file integrity, device seizure readiness, ag-gag exposure assessment
SEO + GEO audit and implementation workflow — Core Web Vitals, HTML structure, semantic writing, E-E-A-T, content intent, Wikipedia/Wikidata, JSON-LD schema, meta tags, crawl budget, robots.txt, sitemap, IndexNow, topic cluster architecture, link building, brand signals, conversion optimization, analytics, internationalization, platform presence, defensive review
SEO + GEO audit and implementation workflow — Core Web Vitals, HTML structure, semantic writing, E-E-A-T, content intent, Wikipedia/Wikidata, JSON-LD schema, meta tags, crawl budget, robots.txt, sitemap, IndexNow, topic cluster architecture, link building, brand signals, conversion optimization, analytics, internationalization, platform presence, defensive review
Layered code review pipeline — automated checks first, then AI-assisted review, then human review focused on Ousterhout red flags, AI failure patterns, silent failures, and advocacy-specific concerns
Spec-first test generation, assertion quality review, mutation testing, five anti-patterns to avoid — for AI-assisted advocacy development where silent test failures mean lost evidence or exposed activists
Plan-before-code workflow — read existing code, write spec, decompose into subtasks, implement and test one at a time, comprehension check before committing
Structured stakeholder interview for advocacy projects — gathers purpose, threat model, coalition needs, legal exposure, user safety requirements, and budget constraints one question at a time
Layered code review pipeline — automated checks first, then AI-assisted review, then human review focused on Ousterhout red flags, AI failure patterns, silent failures, and advocacy-specific concerns
Spec-first test generation, assertion quality review, mutation testing, five anti-patterns to avoid — for AI-assisted advocacy development where silent test failures mean lost evidence or exposed activists
Layered code review pipeline — automated checks first, then AI-assisted review, then human review focused on Ousterhout red flags, AI failure patterns, silent failures, and advocacy-specific concerns
Plan-before-code workflow — read existing code, write spec, decompose into subtasks, implement and test one at a time, comprehension check before committing
Structured stakeholder interview for advocacy projects — gathers purpose, threat model, coalition needs, legal exposure, user safety requirements, and budget constraints one question at a time
Spec-first test generation, assertion quality review, mutation testing, five anti-patterns to avoid — for AI-assisted advocacy development where silent test failures mean lost evidence or exposed activists