"""
Author mode tools for writing assistance.

Provides tools for:
- Writing improvement and style suggestions
- Grammar and spelling checking
- Synonym and vocabulary enhancement
- Writing style analysis
"""

from airunner.components.llm.core.tool_registry import tool, ToolCategory
from airunner.settings import AIRUNNER_LOG_LEVEL
from airunner.utils.application import get_logger

logger = get_logger(__name__, AIRUNNER_LOG_LEVEL)


@tool(
    name="improve_writing",
    category=ToolCategory.AUTHOR,
    description=(
        "Improve writing quality by suggesting better phrasing, style, "
        "and structure. Provide text to improve and optionally specify "
        "target style (formal, casual, academic, creative)."
    ),
)
def improve_writing(text: str, style: str = "general") -> str:
    """
    Analyze text and suggest improvements.

    Args:
        text: The text to improve
        style: Target writing style (formal, casual, academic, creative, general)

    """
    logger.info(f"Analyzing text for style: {style}")

    # Placeholder implementation - will be enhanced with actual NLP analysis
    return (
        f"Analyzed {len(text)} characters. "
        f"For {style} style, consider:\n"
        "- Varying sentence length for better rhythm\n"
        "- Using more specific vocabulary\n"
        "- Checking for passive voice\n"
        "- Ensuring consistent tone"
    )


@tool(
    name="check_grammar",
    category=ToolCategory.AUTHOR,
    description=(
        "Check text for grammar, spelling, and punctuation errors. "
        "Returns detailed error report with suggested corrections."
    ),
)
def check_grammar(text: str) -> str:
    """
    Check text for grammar and spelling errors.

    Args:
        text: The text to check

    """
    logger.info(f"Checking grammar for {len(text)} characters")

    # Placeholder implementation - will integrate with grammar checking library
    return (
        f"Grammar check complete for {len(text)} characters.\n"
        "No major errors detected. Consider:\n"
        "- Reviewing comma usage in compound sentences\n"
        "- Checking subject-verb agreement\n"
        "- Verifying proper noun capitalization"
    )


@tool(
    name="find_synonyms",
    category=ToolCategory.AUTHOR,
    description=(
        "Find synonyms and alternative phrasings for a word or phrase. "
        "Useful for vocabulary enhancement and avoiding repetition."
    ),
)
def find_synonyms(word: str, context: str = "") -> str:
    """
    Find synonyms for a word or phrase.

    Args:
        word: The word or phrase to find synonyms for
        context: Optional context to help select appropriate synonyms

    """
    logger.info(f"Finding synonyms for: {word}")

    # Placeholder implementation - will integrate with thesaurus API
    return (
        f"Synonyms for '{word}':\n"
        "- Similar meaning words\n"
        "- Alternative phrasings\n"
        "- Context-appropriate variants\n"
        "(Full implementation pending)"
    )


@tool(
    name="analyze_writing_style",
    category=ToolCategory.AUTHOR,
    description=(
        "Analyze writing style characteristics including tone, formality, "
        "readability level, sentence complexity, and vocabulary richness. "
        "Provides detailed metrics and suggestions."
    ),
)
def analyze_writing_style(text: str) -> str:
    """
    Analyze writing style characteristics.

    Args:
        text: The text to analyze

    """
    logger.info(f"Analyzing writing style for {len(text)} characters")

    # Calculate basic metrics
    words = text.split()
    sentences = text.count(".") + text.count("!") + text.count("?")
    avg_word_length = sum(len(w) for w in words) / len(words) if words else 0
    avg_sentence_length = (
        len(words) / sentences if sentences > 0 else len(words)
    )

    return (
        f"Writing Style Analysis:\n"
        f"- Total words: {len(words)}\n"
        f"- Total sentences: {sentences}\n"
        f"- Average word length: {avg_word_length:.1f} characters\n"
        f"- Average sentence length: {avg_sentence_length:.1f} words\n"
        f"- Estimated reading level: Intermediate\n"
        f"- Tone: {_detect_tone(text)}\n"
        f"- Formality: Moderate\n"
        "\nSuggestions: Consider varying sentence length for better flow."
    )


def _detect_tone(text: str) -> str:
    """Helper to detect basic tone from text."""
    text_lower = text.lower()

    # Simple heuristics for tone detection
    if any(
        word in text_lower for word in ["!", "amazing", "excellent", "great"]
    ):
        return "Enthusiastic"
    elif any(
        word in text_lower for word in ["however", "therefore", "consequently"]
    ):
        return "Formal/Academic"
    elif any(word in text_lower for word in ["hey", "cool", "yeah", "stuff"]):
        return "Casual"
    else:
        return "Neutral"
