Analyze text for AI-generated patterns and compute a detection risk score.

Scans for AI-associated vocabulary, structural patterns, burstiness, contraction usage, paragraph uniformity, rhetorical questions, first-person voice, and em dash frequency. Returns a comprehensive report with a 0–100 risk score and specific recommendations.

Args: params (AnalyzeTextInput): Contains the text to analyze.

Returns: str: JSON report with risk score, detected patterns, and fix recommendations.

Fast scan for AI-associated vocabulary only — no structural analysis.

Use this for a quick check when you just want to find and replace AI words without running the full analysis pipeline.

Args: params (VocabCheckInput): Contains the text to scan.

Returns: str: JSON with found AI words, their positions, and replacement suggestions.

Analyze AI text and return detailed, step-by-step rewrite instructions.

This tool does NOT rewrite the text itself — it provides a structured action plan that an LLM or human editor can follow to humanize the text. The instructions are tailored to the text type and specific patterns found.

Args: params (HumanizeTextInput): Contains text, text type, and voice preferences.

Returns: str: JSON with analysis results and step-by-step rewrite instructions.

Rewrite AI-generated text to sound human, returning the humanized version.

Applies a deterministic mechanical pass (vocabulary swaps, AI-phrase removal, contraction injection, em-dash cleanup) and returns the rewritten text plus a list of remaining issues that the LLM caller should refine for context.

IMPORTANT — for the model calling this tool: the humanized_text field in the response is a starting point, NOT the final answer. After receiving it, YOU must:

1. Read the polish_instructions field.

2. Refine the text to fix burstiness (vary sentence length aggressively), add first-person voice if missing, and smooth any awkward edits the mechanical pass introduced.

3. Present the FINAL polished version to the user as your reply, along with the before/after risk scores so they can see the improvement.

Args: params (HumanizeTextInput): Text, text type, and voice preferences.

Returns: str: JSON with humanized_text (mechanical rewrite), original_score, rewrite_score, applied_changes, and polish_instructions.

Compare detection metrics between original and rewritten text.

Use after humanizing to verify improvement. Shows side-by-side metrics for burstiness, vocabulary tells, structure, and risk scores.

Args: original (str): The original AI-generated text. rewritten (str): The humanized version.

Returns: str: JSON comparison of detection metrics for both versions.

Return the complete list of AI-associated words and their human replacements.

Use as a reference when manually editing text. Includes both single words and multi-word phrases that trigger AI detection.

Returns: str: JSON with vocabulary ban list and phrase ban list.