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clean-user-facing-text

guillaumemeyer · Документация

Clean and finalize authorized natural-language text intended for readers by auditing suspicious invisible Unicode and rewriting prose while preserving facts, meaning, and the writer's voice. Use when the user asks to clean, humanize, polish, or finalize articles, manuscripts, reports, documentation, emails, product copy, UI text, Markdown, or HTML prose, or when a project rule or instruction file explicitly requires this workflow. Don't use for code-only tasks or undisclosed authorship evasion;

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Теми: agent-skill · ai · anthropic · c2pa · chatgpt · claude · gemini · openai · provenance · synthid · watermark · watermark-detection · watermark-tools · watermarking · watermarks

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Оригинален SKILL.md
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22 657
Лиценз
MIT
Последна проверка на записа
20.09.2026 г.

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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
    
  5. Establish the writing brief before changing prose:

    • use a voice sample only when the user owns it or is authorised to use it; don't imitate another named person
    • when there is no sample, make the prose clear and natural without pretending to imitate a particular person
    • never inject a voice the source lacks: no fake first person ("I've seen this"), invented specifics, forced contrarianism, performed candor, or added stance and personality. Preserve the writer's deliberate rough edges and domain terms rather than scrubbing them
    • keep required disclosures, uncertainty, and the writer's actual point of view
    • pick the voice and domain preset the text fits (see Voice and domain presets); the default is general prose
  6. Layer A — strip artifacts first. For text artifacts or supplied text files, run the deterministic Unicode pass before rewriting, so the rewrite operates on clean, marker-free text:

    PYTHON "$SCRIPTS/clean_text.py" INPUT -o OUTPUT --stats --no-normalize-spaces
    

Целият SKILL.md в GitHub