gabrielmoreira Writing Level Analysis
Measure only text the user authored or explicitly supplied for analysis.
Supported sources
- Text pasted into the conversation
- Local Markdown, text, or documentation files selected by the user
- Git-authored content filtered to commits by the user's configured identity
- Exported prompts or session transcripts supplied as files
Do not fetch private mail, organization records, or remote work systems unless the user explicitly provides and authorizes that data source.
Metrics
Report:
- Flesch-Kincaid Grade Level
- Flesch Reading Ease
- Gunning Fog
- Coleman-Liau
- Automated Readability Index
- Word, sentence, and syllable counts
Use a well-known readability library such as Python textstat. State the
library and version because syllable algorithms differ.
Text preparation
- Keep prose written by the user.
- Remove generated boilerplate, quoted replies, source code, stack traces, tables, URLs, and machine-generated logs unless those are the target.
- Preserve headings and list text when they represent authored prose.
- Analyze each source separately before calculating a combined result.
- Report sample size so a short document is not presented as statistically stable.
Interpretation
- Grade 6-8: broadly accessible
- Grade 9-10: standard professional prose
- Grade 11-12: dense professional or technical prose
- Grade 13+: college-level or highly specialized prose
Readability is not writing quality. Technical vocabulary, identifiers, and necessary precision can raise the score without making the text worse.
Output
Produce:
- A corpus summary
- A per-document metrics table
- Combined metrics recomputed from the complete cleaned corpus
- The clearest and densest samples
- Concrete revision suggestions
- Methodology and exclusions
Never claim ownership of text based only on its location. Confirm authorship or use explicit user-provided files.