blog-analyzelisted

# Blog Analyzer: Quality Audit & Scoring Scores blog posts on a 0-100 scale across 5 categories and provides prioritized improvement recommendations. Includes AI content detection analysis. Works with local files or published URLs. Reference documents (paths from repo root): - `skills/blog/references/quality-scoring.md`: full scoring checklist - `skills/blog/references/eeat-signals.md`: E-E-A-T evaluation criteria - `skills/blog/references/ai-slop-detection.md`: two-tier reflex methodology (v1.8.0) - `skills/blog/references/editorial-heuristics.md`: ordinal 0-4 rubric, P0-P3 severity (v1.8.0, used with `--rubric`) - `skills/blog/references/cognitive-load.md`: per-section concept density (v1.8.0, used with `--cognitive-load`) ## Input Handling - **Local file**: Read the file directly - **URL**: Fetch with WebFetch, extract content - **Directory**: Scan for blog files, audit all (batch mode) - **Flags**: `--format json|table`, `--batch`, `--sort score`, `--rubric`, `--cognitive-load` ### Optional Modes (v1.8.0) - `--rubric`: in addition to the 100-point score, emit the ordinal 0-4 editorial-heuristics rubric with P0-P3 severity tags. See `skills/blog/references/editorial-heuristics.md`. The 100-point JSON schema is preserved; the rubric is added as a sibling `rubric` field. - `--cognitive-load`: run `scripts/cognitive_load.py` against the post and embed the per-section load heatmap as a sibling `cognitive_load` field. See `skills/blog/references/cognitive-load.md`. Both