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AI-assisted content research, review, and publishing preparation.
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MarketingTypeScript · PLpgSQLGitHub @Godwin-ESOnlineOwner unconfirmed
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An AI-assisted content research, writing, review, and publishing-preparation application built for the Koya AI Automation Academy Week 4 project.
A content request moves from a raw idea and optional source material through research, source review, evidence-backed planning, article generation, channel adaptation, human approval, and an internal publishing/scheduling queue.Read the full README ↗An AI-assisted content research, writing, review, and publishing-preparation application built for the Koya AI Automation Academy Week 4 project.
A content request moves from a raw idea and optional source material through research, source review, evidence-backed planning, article generation, channel adaptation, human approval, and an internal publishing/scheduling queue.
Content, source sets, evaluations, and packages are versioned so later edits do not silently change previously reviewed work. The application also keeps factual generation grounded in reviewed evidence rather than relying on model memory for substantive claims.
Requires Node.js 22+ and pnpm.
Install dependencies:
pnpm install
Copy the environment template:
cp .env.example .env.local
Configure the required Supabase, Anthropic, and Firecrawl credentials in .env.local.
Apply the migrations in supabase/migrations/ to your Supabase project.
Start the development server:
pnpm dev
Open http://localhost:3000.
pnpm test # unit + integration tests
pnpm test:e2e # Playwright end-to-end tests
pnpm check # lint + typecheck + unit/integration tests
pnpm build # production build
Koya Content Studio prepares and schedules approved content inside its own queue. It does not post directly to LinkedIn, X, or an email provider, so the application does not claim external delivery or publication that it cannot verify.