New contributor orientation for TaskFlow: write a brief architectural summary based on observed repository artifacts (CLI + REST API in Python; inErrata plugin available).

Architectural Summary (TaskFlow)

• Purpose and scope: TaskFlow provides both a command-line interface and a REST API for managing projects and tasks. The REST API is exposed via uvicorn and exposes an OpenAPI document at /docs, indicating a FastAPI/ASGI-style Python backend.
• System boundaries: A single repository houses both the API server (src.api) and a CLI entrypoint (installed via pip install -e .). The CLI mirrors API capabilities (e.g., create project, add task, list tasks) suggesting a shared domain model and services between CLI and API.
• Key modules (inferred):
  • src.api: API layer implementing HTTP endpoints, request/response models, and orchestration of domain services.
  • CLI components: Command implementations for project and task lifecycle, likely invoking the same domain logic or API layer.
  • Data persistence: Not explicit in current artifacts; expected to be a database-backed storage (relational or document-based) used by the domain layer.
• External/integrations: An inerrata knowledge-graph plugin (opencode-inerrata-plugin) is included to drive proactive MCP tool usage during debugging/orientation flows. It demonstrates a pattern for integrating knowledge graph queries (inerrata_search, inerrata_graph_initialize) and contributing solutions back to the graph.
• Data flow (high level):
  • Client (CLI or API consumer) issues operations against the API; API validates input and forwards to domain services which perform persistence operations and return structured responses.
  • The CLI likely interacts with the backend via library calls or HTTP API, sharing the same domain layer semantics.
  • The inerrata plugin shapes the debugging workflow by ensuring knowledge graph lookups precede code exploration, showing a design that supports tooling-driven debugging and knowledge capture.
• Runtime and deployment hints: Local development uses uvicorn to serve the API, with the README showing typical commands for starting and discovering endpoints. The project uses a Python packaging approach (pip install -e .) indicative of a Python project layout.

What to verify next:

• Inspect src/ for domain models, routers, and DB configuration to confirm the persistence strategy and API surface.
• Locate CLI entry points to map how commands map to domain services or API calls.
• Review tests and any docs to confirm data flows and error handling.