How can I integrate Chief Editor, and what are the costs?

Chief Editor integrates seamlessly into Claude Desktop and Claude Code environments as an MCP server. It offers pre-analysis cost estimation based on word count with a tiered pricing model (small, medium, large).

What specific writing patterns does Chief Editor analyze?

It analyzes text across three dimensions: sloppiness (structural LLM tells, filler, robotic pacing), originality (cliché density), and hype (superlative/intensifier density), each with a 0-1 score.

How does Chief Editor provide detailed feedback on detected patterns?

Beyond general scores, it offers per-pattern annotations ('flags') showing matched text, rule IDs, and reasons. It also includes meta-data like pacing, em-dash, semicolon, superlative, and cliché density labels.

Chief Editor

Name: Chief Editor
Author: quickminds-be

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Analyzes text for AI-generated writing patterns, providing scores for sloppiness, originality, and hype.

The Chief Editor MCP server acts as an AI slop detector, meticulously analyzing text for patterns indicative of AI-generated writing. It evaluates content across three critical dimensions: sloppiness (structural LLM tells, filler phrases), originality (cliché density), and hype (superlative/intensifier density). This tool offers detailed scores and per-pattern annotations, helping users understand the quality and potential AI influence in written content.

주요 기능

01Analyzes text for AI-generated writing patterns across three dimensions: sloppiness, originality, and hype.

02Provides per-pattern annotations ('flags') including positions, matched text, rule IDs, and reasons.

03Includes meta-data such as pacing, em-dash density, semicolon density, superlative density, and cliché density labels.

04Offers pre-analysis cost estimation based on text word count, with tiered pricing.

05Integrates seamlessly into Claude Desktop and Claude Code environments.

060 GitHub stars

사용 사례

01Assessing text for structural LLM tells, filler phrases, robotic pacing, and cliché density.

02Integrating AI text analysis capabilities into development workflows and content publishing pipelines.

03Detecting and evaluating AI-generated content for quality assurance or authenticity verification.