Scan text content for quality issues using deterministic rules and LLM semantic analysis.
npx skills add https://github.com/keji94/content-scanner --skill content-scanner
Please help me install this Agent Skill. Skill: content-scanner Source: https://github.com/keji94/content-scanner/tree/main Command: npx skills add https://github.com/keji94/content-scanner --skill content-scanner
Many writers and editors need an automated way to evaluate text quality, detect rule violations, and receive actionable feedback without manually reviewing every paragraph.
Invoke the scanner with the command scan <content_path> workspace=<workspace_path> to receive a graded quality report.
High-intent search queries and answers about installing and using this skill.
Content quality scanning can be automated by invoking the scanner with a content path and a configured workspace, generating a graded report that evaluates narrative consistency and style issues.
LLM semantic analysis reviews text content paragraph by paragraph to identify subtle narrative problems and logical contradictions that deterministic rule engines might miss.
Yes, Python 3.10 or higher is required to run the deterministic rule engine scripts and execute the zero-cost style and consistency checks for text content.
Yes, you can apply custom rules by specifying a workspace path containing rule and context configurations tailored for novel, tutorial, or general content.
The fix-loop orchestration automatically re-scans text content after suggested edits are applied, ensuring the document converges toward a high quality score.
The content scanner requires jieba for text segmentation and pyyaml to parse workspace rule and context configuration files during the quality analysis process.
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