Clean user-facing text

Apply a final text-hygiene pass to prose the user owns or is authorized to process. Treat Unicode cleanup as deterministic and statistical-watermark reduction as best-effort; never claim that a rewrite proves human authorship or is undetectable. Preserve required academic, legal, platform, and regulatory disclosures.

Workflow

1. Identify the prose that readers will see.

2. Protect non-prose spans:

   • fenced and inline code
   • commands, paths, URLs, identifiers, API names, and exact values
   • formulas, citations, and text the user asks to quote verbatim

3. Preserve every claim, fact, number, name, citation, and requirement. Never invent a detail, name, number, quote, or source to make the prose easier to write or more varied: if a fact is missing, flag the gap rather than fill it. The rewrite may sharpen, compress, or reorder, but it may not add or remove claims.

4. Measure before. Inspect and score the input with the vendored zero-LLM stylometry estimator (see Scoring) and record the score. Read the report's density_tier: rewrite only when it is high; for low or medium, verify the text and otherwise leave the text unchanged. For a flag-only audit that never rewrites, use --audit:

   PYTHON "$SCRIPTS/inspect_text.py" --stylometry --json INPUT
   PYTHON "$SCRIPTS/inspect_text.py" --audit INPUT  # detect-only: lists flagged spans, no rewrite