# `Jido.AI.GoTAgent`
[🔗](https://github.com/agentjido/jido_ai/blob/v2.4.0/lib/jido_ai/agents/strategies/got_agent.ex#L3)

Base macro for Graph-of-Thoughts-powered agents.

Wraps `use Jido.Agent` with `Jido.AI.Reasoning.GraphOfThoughts.Strategy` wired in,
plus standard state fields and helper functions.

## Usage

    defmodule MyApp.ResearchSynthesizer do
      use Jido.AI.GoTAgent,
        name: "research_synthesizer",
        description: "Synthesizes research from multiple perspectives",
        max_nodes: 30,
        max_depth: 6,
        aggregation_strategy: :synthesis
    end

## Options

- `:name` (required) - Agent name
- `:description` - Agent description (default: "GoT agent #{name}")
- `:model` - Model alias or direct model spec (default: :fast, resolved via Jido.AI.resolve_model/1)
- `:max_nodes` - Maximum number of nodes in the graph (default: 20)
- `:max_depth` - Maximum depth of the graph (default: 5)
- `:aggregation_strategy` - `:voting`, `:weighted`, or `:synthesis` (default: `:synthesis`)
- `:generation_prompt` - Custom prompt for thought generation
- `:connection_prompt` - Custom prompt for finding connections
- `:aggregation_prompt` - Custom prompt for aggregation
- `:skills` - Additional skills to attach to the agent (TaskSupervisorSkill is auto-included)

## Generated Functions

- `explore/2,3` - Async: sends prompt, returns `{:ok, %Request{}}` for later awaiting
- `await/1,2` - Awaits a specific request's completion
- `explore_sync/2,3` - Sync convenience: sends prompt and waits for result
- `strategy_opts/0` - Returns the strategy options for CLI access
- `on_before_cmd/2` - Captures request in state before processing
- `on_after_cmd/3` - Updates request result when done

## Request Tracking

Each `explore/2` call returns a `Request` struct that can be awaited:

    {:ok, request} = MyAgent.explore(pid, "Analyze the impact of AI on healthcare")
    {:ok, result} = MyAgent.await(request, timeout: 30_000)

Or use the synchronous convenience wrapper:

    {:ok, result} = MyAgent.explore_sync(pid, "Analyze the impact of AI on healthcare")

## State Fields

The agent state includes:

- `:model` - The LLM model being used
- `:requests` - Map of request_id => request state (for concurrent tracking)
- `:last_request_id` - ID of the most recent request
- `:last_prompt` - The most recent prompt (backward compat)
- `:last_result` - The final result from the last completed exploration (backward compat)
- `:completed` - Boolean indicating if the last exploration is complete (backward compat)

## Task Supervisor

Each agent instance gets its own Task.Supervisor automatically started via the
`Jido.AI.Plugins.TaskSupervisor`. This supervisor is used for:
- LLM streaming operations
- Other async operations within the agent's lifecycle

## Example

    {:ok, pid} = Jido.AgentServer.start(agent: MyApp.ResearchSynthesizer)

    # Async pattern (preferred for concurrent requests)
    {:ok, request} = MyApp.ResearchSynthesizer.explore(pid, "Analyze the impact of AI on healthcare")
    {:ok, result} = MyApp.ResearchSynthesizer.await(request)

    # Sync pattern (convenience for simple cases)
    {:ok, result} = MyApp.ResearchSynthesizer.explore_sync(pid, "Analyze the impact of AI on healthcare")

## Aggregation Strategies

- `:voting` - Selects the most common conclusion among thoughts
- `:weighted` - Weights thoughts by their scores when aggregating
- `:synthesis` - Synthesizes all thoughts into a coherent conclusion (default)

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*Consult [api-reference.md](api-reference.md) for complete listing*