List all available models for a specific provider.

Args:
    provider: The provider to list models for (e.g., "openai", "anthropic")

Returns:
    List of model names available for the specified provider

List all supported LLM providers.

Returns:
    Dictionary with main providers and their shortcuts clearly formatted

Generate business analysis using a specialized Business Analyst persona, with optional decision making.

This tool uses a specialized Business Analyst prompt to analyze business requirements
from a file. It can either use a single model or leverage the team decision-making
functionality to get multiple perspectives and consolidate them.

Args:
    from_file: Path to the file containing the business requirements
    models_prefixed_by_provider: List of models in format "provider:model"
                                (if None, defaults to DEFAULT_MODEL)
    output_dir: Directory where response files should be saved (defaults to input file's directory/responses)
    output_extension: File extension for output files (e.g., 'py', 'txt', 'md')
    output_path: Optional full output path with filename for the output document
    use_decision_maker: Whether to use the decision maker functionality
    decision_maker_models: Models to use if use_decision_maker is True
                         (if None, defaults to DEFAULT_TEAM_MODELS)
    ba_prompt: Custom business analyst prompt template
    decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL)
    decision_maker_prompt: Custom persona prompt template for decision making

Returns:
    Path to the business analysis output file

Generate responses from multiple LLM models and use a decision maker model to choose the best direction.

This tool first sends a prompt from a file to multiple models, then uses a designated
decision maker model to evaluate all responses and provide a final decision.

Args:
    from_file: Path to the file containing the prompt text
    models_prefixed_by_provider: List of team member models in format "provider:model" 
                                (if None, defaults to ["openai:gpt-4.1", "anthropic:claude-3-7-sonnet", "gemini:gemini-2.5-pro"])
    output_dir: Directory where response files should be saved (defaults to input file's directory/responses)
    output_extension: File extension for output files (e.g., 'py', 'txt', 'md')
    output_path: Optional full output path with filename for the persona document
    persona_dm_model: Model to use for making the decision (defaults to DEFAULT_DECISION_MAKER_MODEL)
    persona_prompt: Custom persona prompt template (if None, uses the default)

Returns:
    Path to the persona output file

Generate product management plans using a specialized Product Manager persona, with optional decision making.

This tool uses a specialized Product Manager prompt to create comprehensive product plans
from a file. It can either use a single model or leverage the team decision-making
functionality to get multiple perspectives and consolidate them.

Args:
    from_file: Path to the file containing the product requirements
    models_prefixed_by_provider: List of models in format "provider:model"
                                (if None, defaults to DEFAULT_MODEL)
    output_dir: Directory where response files should be saved (defaults to input file's directory/responses)
    output_extension: File extension for output files (e.g., 'py', 'txt', 'md')
    output_path: Optional full output path with filename for the output document
    use_decision_maker: Whether to use the decision maker functionality
    decision_maker_models: Models to use if use_decision_maker is True
                         (if None, defaults to DEFAULT_TEAM_MODELS)
    pm_prompt: Custom product manager prompt template
    decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL)
    decision_maker_prompt: Custom persona prompt template for decision making

Returns:
    Path to the product plan output file

Generate specification documents using a specialized Spec Writer persona, with optional decision making.

This tool uses a specialized Spec Writer prompt to create comprehensive specification documents
from a file. It can either use a single model or leverage the team decision-making
functionality to get multiple perspectives and consolidate them.

Args:
    from_file: Path to the file containing the requirements or PRD
    models_prefixed_by_provider: List of models in format "provider:model"
                                (if None, defaults to DEFAULT_MODEL)
    output_dir: Directory where response files should be saved (defaults to input file's directory/responses)
    output_extension: File extension for output files (e.g., 'py', 'txt', 'md')
    output_path: Optional full output path with filename for the output document
    use_decision_maker: Whether to use the decision maker functionality
    decision_maker_models: Models to use if use_decision_maker is True
                         (if None, defaults to DEFAULT_TEAM_MODELS)
    sw_prompt: Custom spec writer prompt template
    decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL)
    decision_maker_prompt: Custom persona prompt template for decision making

Returns:
    Path to the specification output file

Read a prompt from a file, send it to multiple LLM models, and write responses to files.

Args:
    file_path: Path to the file containing the prompt text
    models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4").
                                 If None, defaults to ["openai:gpt-4o-mini"]
    output_dir: Directory where response files should be saved (defaults to input file's directory/responses)
    output_extension: File extension for output files (e.g., 'py', 'txt', 'md')
                      If None, defaults to 'md' (default: None)
    output_path: Optional full output path with filename. If provided, the extension
                 from this path will be used (overrides output_extension).

Returns:
    List of file paths where responses were written

Read a prompt from a file and send it to multiple LLM models.

Args:
    file_path: Path to the file containing the prompt text
    models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4").
                                 If None, defaults to ["openai:gpt-4o-mini"]

Returns:
    List of responses, one from each specified model

Send a text prompt to multiple LLM models and return their responses.

Args:
    text: The prompt text to send to the models
    models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4").
                                 If None, defaults to ["openai:gpt-4o-mini"]

Returns:
    List of responses, one from each specified model