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