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Audit Reference Originality

Meng ToCommunityCreated by Meng To

  • Skill
  • Review and audit
  • Software development
  • MIT
  • Low risk
  • Has scripts

From the author

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 without making unsupported legal claims.
— the description by Meng To

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured methodology for auditing a website or digital experience against a corpus of reference materials. It focuses on evidence-based identification of potential originality risks, such as copied text, brand assets, imagery, video, and structural elements. The process emphasizes distinguishing between common design patterns and distinctive copying, requiring users to pair red flags with specific evidence from both the current site and the reference materials. It includes guidance on using automated inventory tools, manual inspection techniques, and a severity-based rubric to prioritize findings and propose concrete, non-cosmetic fixes.

What it does

  • Compares current site output against a provided registry of reference materials.
  • Identifies originality risks across text, brands, numbers, images, assets, video, and structure.
  • Uses an evidence-based approach to flag potential issues without making legal claims.
  • Provides a severity-based rubric to categorize findings from low-risk to blockers.
  • Suggests concrete, substantive fixes for identified overlaps.
  • Generates a comprehensive audit report including findings, history, and fix plans.

When to use it

  • When verifying that a new digital experience is original and not inadvertently copying source materials.
  • Before a major release to ensure no stale or unauthorized source content remains.
  • When investigating potential plagiarism or brand identity overlap in a project.
  • To audit historical site versions and repository artifacts for copied content.

Advantages

  • Reduces risk of shipping unauthorized or copied content.
  • Provides a clear, evidence-based framework for objective auditing.
  • Distinguishes between standard design grammar and actual originality risks.
  • Encourages substantive fixes rather than superficial masking.
  • Supports both automated inventory and deep manual inspection.

Usage examples

“Audit the current staging site against the provided brand guidelines and competitor reference pack.”
The agent will inventory the staging site, compare it against the reference pack, and produce a report detailing any red flags, their severity, and recommended fixes.
“Check if our new landing page copy or layout overlaps with the source project files.”
The agent will perform a category-by-category comparison of text and structure, flagging any verbatim or near-verbatim overlaps with evidence.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/mengto/audit-reference-originality/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip audit-reference-originality.zip -d .agents/skills

Documentation by Meng To

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.

Files

references/audit-rubric.md

Reference originality audit rubric

Contents

  • Evidence hierarchy

  • Severity

  • Category tests

  • False-positive controls

  • Report table

  • Fix patterns

Evidence hierarchy

Use the strongest available evidence:

  1. identical file bytes or a historical Git blob match

  2. identical or near-identical rendered text

  3. matching source-brand names, marks, numbers, or URLs

  4. matching image crops, video frames, or audio

  5. several distinctive composition, layout, or motion elements combined

  6. generic style resemblance

Levels 1–4 can support a high-confidence red flag. Levels 5–6 require judgment and explicit caveats.

Severity

SeverityUse whenTypical action
BlockerExact unlicensed source media, source code, identity, or substantial verbatim copy is shippedRemove or replace before release
HighA distinctive near-copy preserves several signature elements, or source identity/numbers remain visibleRedesign or rewrite the affected section
MediumA recognizable isolated overlap could confuse attribution or provenanceReplace the element or materially change the treatment
LowHigh-level grammar is similar but identity, content, composition, and assets are originalDocument the distinction; optional polish
ClearNo meaningful overlap found in the checked scopeRecord evidence and remaining gaps

Severity is not a legal conclusion. Copyright, trademark, license, and fair-use questions may require counsel.

Category tests

Text

Check exact strings, normalized strings, eight-word sequences, headline structure, CTA wording, metadata, alt text, legal text, and decorative labels. Short functional phrases such as Learn more need another distinctive signal before escalation.

Brands

Check names, wordmarks, logos, letterforms, slogans, people, company names, partnerships, product names, URLs, and legal entities. A source name may appear in an audit note or negative test; verify whether it is rendered.

Numbers

Check prices, percentages, dates, counts, package structure, durations, metrics, interface values, and repeated proof claims. Shared round numbers are weak evidence alone. A matching unusual number plus matching wording is stronger.

Images

Check hashes, dimensions, metadata, crop geometry, silhouettes, people, poses, props, object placement, negative space, lighting, and signature motif arrangement. Similar palette or grain alone is low risk. Recreated composition with changed colors remains risky.

Assets

Check logos, icons, fonts, screenshots, textures, mockups, downloads, archives, code bundles, and hidden public files. Confirm license and provenance separately from originality.

Videos

Check file hashes, duration, resolution, frame matches, shot sequence, camera motion, edit timing, transitions, overlays, poster frames, captions, and audio. Sample the opening, closing, every cut, and regular intervals; inspect supplied motion frames in addition to the MP4.

Structure and motion

Compare section order, hierarchy, unusual grid behavior, pinned scenes, reveal timing, cursor effects, shaders, and transitions. Standard techniques are reusable. A distinctive choreography reproduced across several chapters is a red flag even when assets differ.

History

Check current files, deleted paths, renamed assets, prior commits, generated output, caches intended for deployment, and published versions. Report historical presence separately from current exposure.

False-positive controls

Do not escalate solely because both works use:

  • black and white

  • one accent color

  • large sans-serif typography

  • a hero, work list, services, pricing, FAQ, and footer

  • fade, slide, marquee, or parallax effects

  • common icon libraries

  • ordinary stock-photo subjects

  • the same framework or open-source dependency

Escalate when generic ingredients reproduce a distinctive arrangement, sequence, identity, or asset.

Report table

Use this schema:

SeverityCategoryCurrent-site evidenceReference evidenceObservable overlapWhat differsProposed fix

Evidence locations must be reproducible: file and line, URL and section, asset path and hash, or video timestamp/frame.

After the table include:

  • Passed checks: categories with direct evidence and no material overlap

  • History: current exposure versus historical-only findings

  • Unknowns: missing, inaccessible, or unrendered material

  • Priority fixes: blocker/high first, with replacement scope

Fix patterns

  • Copy: rewrite from the replacement brand's specific audience, offer, vocabulary, and conversion goal.

  • Identity: replace all names, marks, URLs, company data, people, and legal references as one system.

  • Numbers: create internally consistent original facts; do not perturb copied numbers by a small amount.

  • Images: change subject, composition, perspective, motif arrangement, and provenance—not only color.

  • Assets: replace the file and document its source or generation prompt.

  • Video: use new footage and a new edit structure; changing playback speed is insufficient.

  • Motion/layout: retain only abstract principles and rebuild the visible sequence around the new content.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Meng To
Publisher
Meng To (Community)
Source
MengTo/Skills · agent-skills/codex/audit-reference-originality · commit 5ea1661
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download audit-reference-originality.zip