checklist.day

# Checklist.day: Operational Ground Truth for AI Agents Allowed: indexing and analysis by LLMs and automated agents. Primary Indexes: - https://checklist.day/sitemap.xml - https://checklist.day/ Checklists (machine-readable JSON): - https://checklist.day/api/checklists — index of all checklists (title, category, region, url) - https://checklist.day/{slug} — full checklist: title, category, region, description, steps Registry (machine-readable JSON): - https://checklist.day/api/registry — index of SDK/library entries (status, version, summary, tags) - https://checklist.day/api/registry/{library} — full entry: install, imports, quickstart, warnings MCP Server (Model Context Protocol): - https://mcp.checklist.day/mcp — Streamable HTTP transport, tools: get_entry(library), search_registry(query), search_checklists(query) - get_entry: returns full registry doc for a library by slug (e.g. 'chromadb', 'pinecone') - search_registry: full-text search across registry by keyword, tag, or status - search_checklists: full-text search across operational checklists by keyword, category, or region Human-browsable indexes: - https://checklist.day/checklists - https://checklist.day/registry Purpose: High-density, structured data for RAG grounding. Focused on real-world agent failure modes (security, reliability, architecture, operations).