update

README.md

@@ -10,7 +10,7 @@ Julia framework for building agents with tool use and MCP (Model Context Protoco
    ```julia
    agent = YiemAgent.yiemAgent(llmCall; mcpServer=mcpServer, eventSink=yourSink)
    ```
-4. Call `runAgent(agent, message)` then `takeResponse(agent)`
+4. Call `promptAgent(agent, message)` then `takeResponse(agent)`
 
 ## Architecture
 
@@ -20,7 +20,7 @@ src/
 ├── type.jl               # Core types (messages, tools, agent state)
 ├── utils.jl              # Message formatting, context preparation, validation
 ├── agentCore.jl          # Agent loop, tool execution pipeline
-├── api.jl                # Public API (runAgent, takeResponse, followUp, stopAgent)
+├── api.jl                # Public API (promptAgent, takeResponse, followUp, stopAgent)
 └── toolRegistry.jl       # Tool store, MCP discovery, listTools registration
 ```
 
@@ -114,7 +114,7 @@ Tools are discovered dynamically via MCP server:
 
 | Function | Description |
 |----------|-------------|
-| `runAgent(agent, msg)` | Send a message to the agent's input channel |
+| `promptAgent(agent, msg)` | Send a message to the agent's input channel |
 | `takeResponse(agent)` | Block and take the agent's response from output channel |
 | `followUp(agent, msg)` | Send a follow-up message while agent is still processing |
 | `stopAgent(agent)` | Gracefully stop the agent and close channels |
@@ -122,7 +122,7 @@ Tools are discovered dynamically via MCP server:
 ## Agent Lifecycle
 
 1. `yiemAgent()` spawns a background task (`_agentLoop`) listening on `inputChannel` and `followUpChannel`
-2. User messages enter via `runAgent()` or `followUp()`
+2. User messages enter via `promptAgent()` or `followUp()`
 3. `_processMessage()` handles LLM calls, tool execution, and conversation history
 4. Tool execution follows three phases: `prepareToolCall` → `executePreparedToolCall` → `finalizeExecutedToolCall`
 5. `beforeToolCall`/`afterToolCall` hooks allow pre/post-processing of tool calls