> ## Documentation Index
> Fetch the complete documentation index at: https://docs.compose.market/llms.txt
> Use this file to discover all available pages before exploring further.

# Strongly Typed Execution

> Where Manowar uses typed contracts instead of prompt-only control.

Manowar lets the model reason, but keeps execution contracts typed. The clearest example is the Manowar Agent Loop (`mal`) harness.

## Typed Surfaces

| Surface     | Type source                                          | Runtime behavior                                                     |
| ----------- | ---------------------------------------------------- | -------------------------------------------------------------------- |
| Tools       | JSON Schema or Zod                                   | Converted into OpenAI-style function tools.                          |
| MAL plans   | `harness/swarm/types.ts` plus interpreter validation | Parsed from YAML/JSON and dispatched by closed `op` enum.            |
| Subagents   | `SubAgentSpec`                                       | Requires deployed `agentWallet`, explicit model, budgets, and depth. |
| Memory loop | `AgentMemoryScope` and workflow response types       | Enforces scope and step names.                                       |
| Telemetry   | `UsageRecord`, `FeedbackRecord`, `RunMetadataRecord` | Normalizes provider usage into runtime records.                      |

## MAL Ops

| Op           | Purpose                                      |
| ------------ | -------------------------------------------- |
| `task`       | Spawn a focused registered subagent.         |
| `delegate`   | Call a registered deployed agent.            |
| `fanout`     | Run branches with controlled concurrency.    |
| `tool`       | Call a registered tool directly.             |
| `if`         | Branch on a safe mini expression.            |
| `loop`       | Repeat a bounded block.                      |
| `scratch`    | Read/write private run state.                |
| `synthesize` | Combine saved values with an explicit model. |
| `stop`       | Return final output.                         |
| `ask_user`   | Request host-provided input.                 |

## Example

```yaml theme={null}
description: "Research, draft, and synthesize"
budget:
  maxDepth: 3
  maxWallMs: 300000
steps:
  - op: delegate
    saveAs: research
    agentWallet: "0x1111111111111111111111111111111111111111"
    prompt: "Collect source-backed notes for the topic."

  - op: synthesize
    saveAs: answer
    from: ["research"]
    model: "gpt-5.5"
    instruction: "Write a concise answer using only the saved notes."

  - op: stop
    output: "{{answer}}"
```

The interpreter validates the plan, resolves `{{step.path}}` references, executes each step, and records step results. The model does not parse an English instruction manual on every step.

## Related

* [Harness planning](/manowar/harness/planning)
* [Harness architecture](/manowar/harness/architecture)
* [Tool surface](/manowar/tools/overview)