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Audit Reference Originality skill

Audit a website or digital experience against its supplied source references for originality and plagiarism risk. Use when Codex must compare current or historical site output with reference pages, capture packs, screenshots, copy, brands, numbers, images, assets, videos, layouts, motion, or code; raise evidence-backed red flags; distinguish common visual grammar from distinctive copying; and propose concrete fixes w

$npx skills add MengTo/Skills --skill audit-reference-originality
View this skill on GitHubMengTo/Skills/agent-skills/codex/audit-reference-originality/SKILL.md
Pack stars
7,353
Pack installs
246k
Alyn Score
76/99
Updated
2 days ago
License
MIT
– views – installs via Alyn

Install Audit Reference Originality

Pick your agent. Every command is ready to paste.

$npx skills add MengTo/Skills --skill audit-reference-originality

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads audit-reference-originality when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the audit-reference-originality skill”. In Codex, type $audit-reference-originality.

The skill itself

SKILL.md

FolderGitHub

Audit Reference Originality

Compare the shipped experience with the complete reference corpus. Treat the audit as an evidence exercise, not a vibe check.

Preserve the audit boundary

  • Audit only unless the user also asks for fixes.
  • Call findings originality risks, overlaps, or red flags; do not declare legal plagiarism from visual similarity alone.
  • Pair every red flag with exact current-site evidence and exact reference evidence.
  • Keep fact, inference, and unknown access separate.
  • Do not clear a site after checking only its homepage screenshot.

1. Build the source registry

Start with the materials explicitly supplied in the task or recorded by the project:

  • manifests, prompt packs, and originality matrices
  • representative stills, full-page captures, and section crops
  • MP4s and extracted motion frames
  • reference URLs and named creators
  • source brand assets, copy, numbers, screenshots, and downloads
  • project briefs, IMAGE_CREDITS.md, licenses, and attribution files

Prefer local evidence captured at the time of the brief. Use a live reference only to fill a real gap, because it may have changed. Record each reference's path or URL, role, date when known, and which categories it can prove.

Stop and report an access gap when a promised reference is missing. Do not silently reduce a full-page or motion audit to one cover image.

2. Inventory the current site and its history

Inspect:

  • rendered text, metadata, navigation, calls to action, legal copy, and hidden accessible labels
  • brand names, wordmarks, logos, icons, people, companies, URLs, and product/interface data
  • prices, metrics, dates, counts, percentages, package names, and repeated proof claims
  • every rendered image, background, texture, screenshot, font, logo, icon, audio file, and downloadable asset
  • every video, poster, frame sequence, shot order, transition, duration, and playback treatment
  • layout hierarchy, section order, distinctive compositions, typography behavior, motion grammar, shaders, cursor effects, and interaction sequences
  • current source, built output when available, asset provenance, and repository history

Do not trust filenames as proof of originality. Inspect the bytes, visible result, and history. Search renamed, deleted, and replaced files with git log, git show, git log -S, and git log --all --name-status.

Run the deterministic inventory helper when local files are available:

python <skill-dir>/scripts/build_evidence_inventory.py \
  --site <site-root> \
  --reference <reference-file-or-directory> \
  --reference <another-reference> \
  --output <temporary-output.json>

The helper finds current and historical exact-file matches, suspicious basename reuse, normalized text overlap, and repeated number tokens. Treat its output as leads for human review, not an automatic verdict.

3. Compare category by category

Read references/audit-rubric.md before judging findings.

Audit at least these categories:

  1. Text — headlines, body copy, labels, CTAs, captions, legal text, alt text, metadata, and decorative wording.
  2. Brands — names, marks, wordmarks, proprietary icons, people, companies, partnerships, URLs, and distinctive verbal identity.
  3. Numbers — metrics, percentages, prices, dates, counts, plan structures, durations, and interface values.
  4. Images — exact files, crops, generated derivatives, screenshots, people, poses, objects, signature compositions, and color treatment.
  5. Assets — fonts, icons, logos, textures, mockups, downloads, code bundles, and third-party media with unclear provenance.
  6. Videos — exact files, frames, shots, timing, camera moves, edit rhythm, transitions, overlays, posters, and audio.
  7. Structure and motion — section order, unusual layout devices, pinned sequences, cursor interactions, shaders, and combinations of signature elements.
  8. History — copied material that was later renamed, recolored, cropped, hidden, deleted, or replaced.

Common patterns such as black backgrounds, large sans-serif type, ordinary pricing tables, standard fade-ins, or a conventional footer are not red flags by themselves. Escalate combinations of distinctive elements or direct evidence.

4. Triangulate every red flag

For each candidate:

  1. Identify the current-site artifact and location.
  2. Identify the exact reference artifact and location.
  3. State the observable overlap without guessing intent.
  4. State what differs.
  5. Assign severity using the rubric.
  6. Propose the smallest fix that breaks the overlap while preserving the site's goal.

Use hashes for exact files, normalized excerpts for copy, side-by-side crops for imagery, and matched timestamps or frames for video. A source-brand string found only in a test that explicitly forbids it is not a shipped-copy violation; explain context.

5. Propose fixes

Prefer concrete replacements:

  • rewrite source-like copy from the new brand's audience, offer, and vocabulary
  • replace names, URLs, logos, people, metrics, dates, plan names, and legal text
  • regenerate or license new imagery with a materially different subject, composition, and motif arrangement
  • replace copied assets and document provenance
  • re-cut videos with new shots, timing, transitions, overlays, and audio
  • reorder or redesign distinctive section and motion sequences
  • remove stale source material from current output and, when required, repository history or published artifacts

Do not recommend cosmetic recoloring as a fix for copied identity, copy, media, or composition.

6. Report the result

Lead with one verdict:

  • Clear in checked scope
  • Clear with low-risk similarities
  • Changes recommended
  • Block release
  • Blocked by missing evidence

Then provide:

  1. checked source registry
  2. red-flag table ordered by severity
  3. category pass list
  4. history findings
  5. access gaps and unproven areas
  6. prioritized fix plan

Include a row even when a high-risk category could not be checked. Never turn missing evidence into a pass.

Completion checks

  • Every supplied reference form was inspected.
  • Rendered output and source were both checked.
  • Text, brands, numbers, images, assets, videos, structure/motion, and history were covered.
  • Every red flag cites two evidence locations.
  • Exact matches are distinguished from stylistic similarity.
  • Proposed fixes replace the copied element rather than disguising it.
  • The report states what remains unverified.

Tips for Audit Reference Originality

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • This skill ships scripts. Read them before the first run, and run it in a project without secrets first.
  • • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
  • • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Audit Reference Originality

What does the Audit Reference Originality skill do?

Audit a website or digital experience against its supplied source references for originality and plagiarism risk. Use when Codex must compare current or historical site output with reference pages, capture packs, screenshots, copy, brands, numbers, images, assets, videos, layouts, motion, or code; raise evidence-backed red flags; distinguish common visual grammar from distinctive copying; and propose concrete fixes w

How do I install Audit Reference Originality?

Run "npx skills add MengTo/Skills --skill audit-reference-originality" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Audit Reference Originality work in Cursor and Codex?

Yes. Audit Reference Originality uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Audit Reference Originality free?

Audit Reference Originality is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Audit Reference Originality?

Audit Reference Originality is published by MengTo in the MengTo/Skills repository, together with 29 other skills.

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