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/anti-detection-writing

@182abd0
Run it yourself

Polish AI-written replies, emails, articles, and documentation for smoother flow and better human readability. Preserve meaning and factual accuracy; when requested, test revisions with GPTZero or another detector and work toward lower AI-detection scores.

Use this Skill: https://skilld.dev/gh/dexhunter/anti-detection-writing-skill/anti-detection-writing

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

referencesreceipt-format.md

≈856 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Strict receipt format for new scans

scripts/validate_receipt.py ANSWER.txt RECEIPT.json checks a local receipt. Python 3.10+ is required, with no third-party Python dependencies. It makes no network requests and is not a detector. The historical public dataset has a separate format and checker.

For a declared prose-only scan, ANSWER.txt and receipt answer contain the exact prose sent to the detector. Keep a separate scope record with the full reviewed message's hash, prose hash and approved code exclusions. This checker validates the submitted artifact, not the exclusion decision or the full-message association. Its byte checks are unchanged; do not present the result as a whole-message score.

A 100% AI result is valid measurement data. To apply an already requested condition, use --max-ai-exclusive 100. Omitting that option checks evidence consistency only. Neither result grants publication permission or establishes quality or human authorship.

Save these artifacts in a private directory:

  • The exact final answer bytes, submitted text, and effective editor text.
  • A full accessibility snapshot of the completed result containing the Basic Scan heading, displayed model, AI/Mixed/Human buttons, freshness indicator, and any short-text warning.
  • A JSON receipt with the following shape. Replace every placeholder with an observed value or a SHA-256 computed from exact file bytes.
{
  "schema_version": 1,
  "service": "GPTZero",
  "mode": "Basic Scan",
  "model": "4.9b",
  "status": "complete",
  "text_up_to_date": true,
  "entry_mode": "verbatim",
  "observed_at": "2026-09-06T09:00:00Z",
  "ai_percent": 100,
  "mixed_percent": 0,
  "human_percent": 0,
  "short_text_warning": false,
  "answer": {"path": "answer.txt", "sha256": "REPLACE_WITH_HASH"},
  "submitted": {"path": "submitted.txt", "sha256": "REPLACE_WITH_HASH"},
  "editor": {"path": "editor.txt", "sha256": "REPLACE_WITH_HASH"},
  "visible_result": {"path": "result.txt", "sha256": "REPLACE_WITH_HASH"}
}

The timestamp and scores above illustrate the schema; they are not a real scan receipt. Model values must come from the current UI, not this example. The checker requires a timezone and verifies the saved UI's model and scores. It does not establish when the service was accessed.

Artifacts must remain inside the receipt directory; absolute paths, parent traversal, and escaping symlinks are rejected. File hashes are exact, including trailing newlines. Between answer/submitted/editor files only CRLF versus LF line endings may differ. Spaces, code indentation, punctuation, and line counts must remain intact. Rendered Markdown is deliberately unsupported. Keep final prose in a verbatim entry mode or report the representation limitation; do not loosen comparisons to hide input changes.

The visible-result parser supports the accessibility snapshot shape observed during development: heading "Basic Scan" [level=1], generic: Model ..., button "AI ...%" (and Mixed/Human), and generic: Text up-to-date. A changed UI may need a reviewed parser update. Missing or ambiguous controls fail closed. A saved snapshot and its hashes can still be fabricated; this is a consistency check, not service authentication.

Never publish the raw account snapshot by default. A public study should export only needed fields and inputs with source attribution, as described in the measurement instructions.

Source: SKILL.md on GitHub

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

No alerts1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The anti-detection-writing skill focuses on polishing AI-generated text for readability while maintaining factual accuracy. It provides clear safety boundaries, explicitly forbidding the use of deceptive obfuscation techniques like invisible characters. The skill includes a secure local validation script for audit trails that does not require network access or external dependencies.

  • Socket1mo

    No alerts

  • Snyk1mo

    Risk: LOW · No issues

Signed by skilld at 182abd0. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

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