agentleFS
danieletetidanieleteti/delphimvcframework/.agents/skills/clean-user-facing-text/SKILL.md

clean-user-facing-text

Skill1.4k starsChanged 17 days agoApache-2.0View on GitHub

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; leave code, commands, identifiers, paths, APIs, formulas, citations, required disclosures, and verbatim quotations unchanged.

4 other projects use a version of this, 4 of them edited.

Trending

Quiet since December.thin dataabout the whole repository

Dec 2025: 1 mentionJan 2026: 0 mentionsFeb 2026: 0 mentionsMar 2026: 0 mentionsApr 2026: 0 mentionsMay 2026: 0 mentionsJun 2026: 0 mentionsJul 2026: 0 mentionsAug 2026: 0 mentionsSep 2026: 0 mentionsOct 2026: 0 mentionsNov 2026: 0 mentions
Dec 2025Jun 2026Nov 2026
Mentions a month of the danieleteti/delphimvcframework repository that our weekly crawl found: only 12 in all, so this is a hint, not a trend. There is no adoption data for this file yet.

Most recently taken up by

Who's talking about danieleteti/delphimvcframework

The biggest 5 of 12 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 12

Talked about on GitHub, Stack Overflow and Hacker News (12 times).

On GitHub · 6

1 more on GitHub

On Hacker News · 1

The file

We split this skill into the rules it gives an agent

12 rules. 8 are common, 0 are distinctive, and 4 are very specific to this project.

  • 8

    Common

    Most of the 4 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    use a voice sample only when the user owns it or is authorised to use it.

    line 19
  2. Common:

    when there is no sample, make the prose clear and natural without pretending to imitate a particular person

    line 20
  3. Common:

    keep required disclosures, uncertainty, and the writer's actual point of view

    line 21
  4. Common:

    keep the concrete details and judgement that make the text recognisable as the writer's

    line 25
  5. Common:

    treat unusual grammar, repetition, directness, and phrasing as possible voice or accessibility choices.

    line 26
  6. Common:

    do not add or remove claims merely to increase variation

    line 29
  7. Very specific:

    Use the available Python 3 launcher for the platform.

    line 39
  8. Very specific:

    Use - for stdin. Prefer a new *.cleaned.* output unless the user explicitly requests in-place editing.

    line 51
  9. Very specific:

    Use --no-normalize-spaces by default so NBSP, narrow no-break spaces, figure spaces, and CJK ideographic spaces retain their layout …

    line 53
  10. Very specific:

    Do not use --aggressive-homoglyphs, --nfkc, or --strip-emoji-glue unless the user requests aggressive normalization and accepts possible …

    line 55
  11. Common:

    When prose and code are mixed, rewrite prose only.

    line 63
  12. Common:

    When the user asks for an audit, distinguish:

    line 67

“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.
  4. 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
    • keep required disclosures, uncertainty, and the writer's actual point of view
  5. Rewrite the remaining prose once:
    • vary clause order, sentence boundaries, rhythm, connectors, and function words
    • replace formulaic transitions and filler with direct, natural wording
    • keep the concrete details and judgement that make the text recognisable as the writer's
    • treat unusual grammar, repetition, directness, and phrasing as possible voice or accessibility choices; change them only when the user asks or when they create a clear reading problem
    • preserve the requested language, tone, structure, and formatting; never translate unless asked
    • for non-English text, use fluent constructions native to that language rather than English sentence patterns
    • do not add or remove claims merely to increase variation
  6. For text artifacts or supplied text files, run the deterministic Unicode pass after rewriting.
  7. Return only the polished result unless the user asks for an audit or explanation.

For practical guidance on preserving a writer's voice and removing formulaic prose, read references/writing-in-your-voice.md whenever the user asks to retain or adjust voice.

Deterministic Unicode pass

Resolve SCRIPTS to this skill's scripts/ directory. Use the available Python 3 launcher for the platform. Replace PYTHON below with python3 on most macOS/Linux systems, py on Windows, or another verified Python 3 command.

Inspect first when editing an existing file:

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

Use - for stdin. Prefer a new *.cleaned.* output unless the user explicitly requests in-place editing.

Use --no-normalize-spaces by default so NBSP, narrow no-break spaces, figure spaces, and CJK ideographic spaces retain their layout semantics. Normalize spaces only when the user requests it.

Do not use --aggressive-homoglyphs, --nfkc, or --strip-emoji-glue unless the user requests aggressive normalization and accepts possible changes to multilingual text, emoji, directionality, or typography.

The scripts support plain text, source text, Markdown, and HTML source as text. For mixed Markdown or HTML, inspect hit positions first. If a hit falls inside protected code, attributes, or another non-prose span, do not run whole-file cleanup; clean only the prose segments or leave that hit unchanged. Do not pass binary containers such as PDF, DOCX, images, or archives.

For a chat-only response that is not written to a file, perform the rewrite workflow directly. Do not claim that the chat response received a deterministic post-send Unicode filter.

Code boundary

When prose and code are mixed, rewrite prose only. Never rename variables, alter string literals, reformat code, or change executable output as part of this skill. If a Markdown or HTML file contains executable snippets, preserve those spans byte-for-byte whenever practical.

Reporting

When the user asks for an audit, distinguish:

  • Verifiable: Unicode characters removed or replaced, with script counts.
  • Best-effort: prose rewritten to alter token and syntax patterns.
  • Not established: official detector evasion, human authorship, or removal of a vendor's secret-key watermark.

For technical background, read references/watermark-notes.md. For misuse or disclosure questions, read references/responsible-use.md.

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