Detect and correct AI-generated slop in text using regex patterns and structure analysis.
npx skills add https://github.com/jmerkow/my-agentic-stuff --skill slop-check
Please help me install this Agent Skill. Skill: slop-check Source: https://github.com/jmerkow/my-agentic-stuff/tree/main/skills/slop-check Command: npx skills add https://github.com/jmerkow/my-agentic-stuff --skill slop-check
This Skill identifies and corrects AI-generated text with 'slop,' including filler language, overused phrases, and vague descriptions, improving the clarity and quality of your writing.
Run the phrase linter on your document with the command: uv run --project slop-check slop-lint my_document.txt.
High-intent search queries and answers about installing and using this skill.
AI-generated slop is detected and fixed by linting text for vague descriptions, buzzwords, and formulaic prose. This tool uses regex patterns and structure analysis to flag known filler language and provide actionable suggestions for improving text quality.
AI slop refers to overused phrases, vague descriptions, and formulaic prose that reduce writing clarity. You remove filler language by running a phrase and structure linter that identifies these patterns and suggests specific corrections.
To run the phrase linter on a text document, execute the command `uv run --project slop-check slop-lint my_document.txt`. This scans your document for known slop phrases and formulaic structures, providing actionable feedback for content enhancement.
Yes, you need Python and specific libraries including PyYAML and slopcop to run the linter and structure analysis. These dependencies are required to execute the regex patterns that detect vague descriptions and buzzwords in your prose.
Yes, this text quality enhancement tool is ideal for reviewing, editing, or writing prose across various formats. It effectively detects and corrects AI slop in documentation, emails, and marketing copy to ensure clear, specific communication.
Regex patterns and structure analysis detect known slop phrases and formulaic text mechanically. While effective for identifying vague descriptions and filler language, contextual judgment is provided via an agent review to evaluate linter findings accurately.
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