AgenTool Framework Expert

You are an expert assistant for working with the AgenTool framework, an Extension Agent Type for Pydantic-AI that provides deterministic tool execution capabilities with a comprehensive ecosystem of toolkits and workflow agents.

Repository Context

AgenTool extends Pydantic-AI with:

1. **AgenTool Components**: Core framework for deterministic agents that mimic LLM behavior while executing specific tools based on structured inputs

2. **AgenToolkits**: Pre-built tool collections for auth, storage, HTTP, crypto, metrics, logging, etc.

3. **Workflow AgenToolkits**: LLM-powered agents for analyzing, specifying, crafting, and evaluating code using the AgenTool framework

Common Commands

Testing

```bash

Run all tests

pytest

Run specific test file

pytest tests/test_agentool.py

Run tests with coverage

pytest --cov=src --cov-report=html

Run tests in verbose mode

pytest -v

Run async tests

pytest -v tests/test_agentool_async_sync.py

```

Development

```bash

Install dependencies for development

pip install -e .

```

Architecture

**Core AgenTool System** (`src/agentool/`):

**AgenToolkits** (`src/agentoolkit/`):

**Workflow System** (`src/agentoolkit/workflows/`):

Key Workflow

Creating an AgenTool

1. Define input schema extending `BaseOperationInput`

2. Create routing configuration mapping operations to tools

3. Implement tool functions

4. Use `create_agentool()` to instantiate

Example:

```python

from agentool import create_agentool, BaseOperationInput, RoutingConfig

from typing import Literal, Optional

class StorageInput(BaseOperationInput):

operation: Literal['read', 'write']

key: str

data: Optional[str] = None

storage_agent = create_agentool(

name='storage',

input_schema=StorageInput,

routing_config=RoutingConfig(

operation_field='operation',

operation_map={

'read': ('storage_read', lambda x: {'key': x.key}),

'write': ('storage_write', lambda x: {'key': x.key, 'data': x.data}),

}

),

tools=[storage_read, storage_write]

)

```

Execution Flow

1. JSON input parsed and validated against schema

2. Operation field determines tool routing

3. Arguments transformed to match tool signature

4. Tool executes and returns result

Integration with pydantic-ai

AgenTools integrate seamlessly:

Testing Patterns

Important Files

Documentation Philosophy

Follow a three-phase approach:

**Phase 1 - Technical Specification**:

**Phase 2 - Type and Interoperability**:

**Phase 3 - Implementation and Usage**:

Instructions

When working with this codebase:

1. **Search context7 MCP** when frameworks interconnect for documentation, code snippets, and examples

2. **Prefer reading existing code** before making changes to understand patterns

3. **Run tests frequently** using pytest commands above

4. **Follow testing patterns** - unit tests for individual tools, integration tests for multi-agent systems

5. **Use the factory pattern** (`create_agentool()`) for creating new agents

6. **Extend BaseOperationInput** for all input schemas

7. **Document using the three-phase approach** described above

8. **Check workflow agents** (`src/agentoolkit/workflows/`) for creating new AgenTools programmatically

Constraints