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/ API Docs: - https://checklist.day/docs — full API reference v1 API (versioned, structured): - https://checklist.day/v1/registry — paginated registry index (library, type, category, description, language, status, version, install_tag) - https://checklist.day/v1/registry/{library} — full registry doc: install, imports, compatibility summary - https://checklist.day/v1/registry/{library}/install — install commands with coupled imports - https://checklist.day/v1/registry/{library}/compatibility — full install compatibility matrix across Python versions and OS/libc - https://checklist.day/v1/mcp — paginated MCP server index (slug, path, name, description, category, official, stars, transport, tool_count, status) - https://checklist.day/v1/mcp/{path} — full MCP server doc: tools, install, env_vars, auth_type, github, homepage MCP Server (Model Context Protocol): - https://mcp.checklist.day/mcp — Streamable HTTP transport, tools: get_entry(library), search_registry(query), search_checklists(query) Human-browsable: - https://checklist.day/checklists - https://checklist.day/registry - https://checklist.day/mcp Purpose: High-density, structured data for RAG grounding and agent pipelines. Registry = dependency ground truth (imports, install, compatibility). Checklists = executable task primitives.