# Architecture Decisions

This document records deliberate "won't do" decisions for the project. These are features we evaluated and chose NOT to implement — not because they're bad ideas, but because they conflict with our positioning as the **simplest multi-agent framework**.

If you're considering a PR in any of these areas, please open a discussion first.

## Won't Do

### 1. Agent Handoffs

**What**: Agent A transfers an in-progress conversation to Agent B (like OpenAI Agents SDK `handoff()`).

**Why not**: Handoffs are a different paradigm from our task-based model. Our tasks have clear boundaries — one agent, one task, one result. Handoffs blur those boundaries and add state-transfer complexity. Users who need handoffs likely need a different framework (OpenAI Agents SDK is purpose-built for this).

### 2. State Persistence / Checkpointing

**What**: Save workflow state to a database so long-running workflows can resume after crashes (like LangGraph checkpointing).

**Why not**: Requires a storage backend (SQLite, Redis, Postgres), schema migrations, and serialization logic. This is enterprise infrastructure — it triples the complexity surface. Our target users run workflows that complete in seconds to minutes, not hours. If you need checkpointing, LangGraph is the right tool.

**Related**: Closing #20 with this rationale.

### 3. A2A Protocol (Agent-to-Agent)

**What**: Google's open protocol for agents on different servers to discover and communicate with each other.

**Why not**: Too early — the spec is still evolving and adoption is minimal. Our users run agents in a single process, not across distributed services. If A2A matures and there's real demand, we can revisit. Today it would add complexity for zero practical benefit.

### 4. MCP Integration (Model Context Protocol)

**What**: Anthropic's protocol for connecting LLMs to external tools and data sources.

**Why not now**: Our `defineTool()` API lets users wrap any external service as a tool in ~10 lines of code, and adding MCP would introduce `@modelcontextprotocol/sdk` as a new dependency plus transport layer management, breaking our 3-dependency minimal principle. However, the MCP tool ecosystem has grown significantly — many services now ship MCP servers directly, and asking users to re-wrap each one via `defineTool()` creates unnecessary friction. **This decision may be revisited** when community demand is clear or a lightweight integration approach emerges (e.g., optional peer dependency).

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*Last updated: 2026-04-07*