Plagiarism Checker logo

Plagiarism Checker

Organization
bitwize-music-studio
plagiarism-checker

Scans lyrics for phrases that may match existing songs using web search and LLM knowledge. Use before release to check for unintentional borrowing.

Overview

Publisherbitwize-music-studio
Repositoryclaude-ai-music-skills
Skill nameplagiarism-checker
Stars
546
Forks
130
Bundled files
Instructions only
LicenseCC0-1.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bitwize-music-studio on GitHub. Read the source before you install it.

Installation

Install the Plagiarism Checker AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bitwize-music-studio/claude-ai-music-skills/tree/main/skills/plagiarism-checker
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bitwize-music-studio/claude-ai-music-skills.git /tmp/claude-ai-music-skills
mkdir -p .claude/skills
cp -r /tmp/claude-ai-music-skills/skills/plagiarism-checker .claude/skills/plagiarism-checker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plagiarism Checker in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Plagiarism Checker on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Plagiarism Checker is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Your Task

Target: $ARGUMENTS

  1. Get lyrics for the specified track(s)
  2. Extract distinctive phrases using MCP tool
  3. Web search top phrases for matches against known songs
  4. Use LLM knowledge to independently flag similarities
  5. Generate structured risk report

Plagiarism Checker

You scan lyrics for phrases that may unintentionally echo existing songs. This is a quality check, not a legal tool — it catches borrowing early so the writer can revise before release.


Workflow

Step 1: Get Lyrics

  • Use extract_section(album_slug, track_slug, "streaming") to get streaming lyrics (preferred — no phonetic spellings that confuse web searches)
  • If streaming lyrics empty, fall back to extract_section(album_slug, track_slug, "lyrics") for Suno lyrics
  • If raw text was provided instead of album/track reference, use that directly

Step 2: Extract Distinctive Phrases

Call extract_distinctive_phrases(text, max_phrases=15, include_raw_lines=False) MCP tool. This returns:

  • Distinctive 4-7 word n-grams ranked by section priority (top 15)
  • Pre-formatted search suggestions with quoted phrases + "lyrics"
  • Common cliches already filtered out

Step 3: Web Search

  • Search the top 10-15 search_suggestions returned by the tool using WebSearch
  • For short lyrics (<100 words), limit to 5-8 searches
  • Look for results that reference specific songs by title/artist
  • Skip results that are:
    • Lyrics aggregator sites listing hundreds of matches (too generic)
    • Dictionary/reference pages
    • The user's own published work

Step 4: Deep Compare

For any search result that names a specific song:

  1. WebFetch the lyrics page
  2. Compare the matching section against the user's lyrics
  3. Check if the match is:
    • Exact consecutive words (5+) — HIGH risk
    • Partial overlap (4 words) — MEDIUM risk
    • Thematic similarity only — LOW risk

Step 5: LLM Knowledge Check

Independently scan ALL lines of the lyrics (not just extracted phrases) using your training knowledge:

  • Flag any line that closely resembles a well-known song lyric
  • Include the suspected source song and artist
  • Note whether the similarity is in words, melody hook phrasing, or concept

Step 6: Generate Report


Risk Levels

LevelCriteriaAction
HIGH5+ consecutive matching words from a known song, especially chorus/hookRewrite the line immediately
MEDIUM4-word match from known song, or structural similarity flagged by LLMReview and consider rewording
LOWCommon phrasing overlap, likely coincidenceNote for awareness, no action needed

Output Format

PLAGIARISM CHECK REPORT
Album: [Album Name]
Track: [Track Title]
Date: [Scan Date]

PHRASES SEARCHED: [N]
WEB MATCHES FOUND: [N]
LLM FLAGS: [N]

FINDINGS:
------------------------------------------------------------------------

[HIGH] Line 12 (Chorus): "burning shadows fall tonight across the wire"
  Match: "Shadows Fall Tonight" by [Artist] — 5 consecutive words match chorus
  Source: [URL]
  Recommendation: Rewrite this line to avoid direct overlap

[MEDIUM] Line 24 (Verse 2): "walking through the ruins of the empire"
  Similarity: Resembles "Empire" by [Artist] — similar phrasing in bridge
  Source: LLM knowledge
  Recommendation: Consider rewording if concerned

[LOW] Line 8 (Verse 1): "the city sleeps beneath the stars"
  Note: Generic night imagery, appears in many songs
  Recommendation: No action needed

------------------------------------------------------------------------

SUMMARY:
  HIGH risk findings: 1
  MEDIUM risk findings: 1
  LOW risk findings: 1

VERDICT: NEEDS REVIEW
  1 high-risk match requires attention before release.

COMMON PHRASES FILTERED: [N] (not searched — too generic to flag)

Verdicts

VerdictCriteria
CLEARNo HIGH or MEDIUM findings
NEEDS REVIEWAny MEDIUM findings, or 1 HIGH finding
REWRITE REQUIRED2+ HIGH findings

Important Notes

  • This is not a legal tool. It catches likely borrowing, not copyright infringement. Only a lawyer can determine infringement.
  • Streaming lyrics preferred. Suno lyrics contain phonetic respellings (e.g., "Seh-KYOOR-ih-tee" for "security") that will produce garbage web search results.
  • Common cliches are pre-filtered. The MCP tool removes ~75 ubiquitous phrases ("break my heart", "falling in love", etc.) before returning results. These are too common to flag.
  • Web searches may fail. If WebSearch is unavailable or rate-limited, proceed with LLM knowledge check only and note the limitation in the report.
  • Not a pre-generation gate. This check is too slow (web searches) and too unreliable (search availability) to block generation. Run it before release, not before Suno.

Running for Full Album

When given an album slug without a specific track:

  1. List all tracks via list_tracks(album_slug)
  2. Run the check for each track with status "In Progress", "Generated", or "Final"
  3. Skip tracks with status "Not Started" or "Sources Pending"
  4. Aggregate findings into a single album-level report with per-track sections

Example Invocations

/plagiarism-checker dark-tide
/plagiarism-checker dark-tide 03-the-wire

Frequently asked questions

What does the Plagiarism Checker AI skill do?

Scans lyrics for phrases that may match existing songs using web search and LLM knowledge. Use before release to check for unintentional borrowing.

Why use Plagiarism Checker on TypingMind?

Because you install it once and use it with any model. Plagiarism Checker is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Plagiarism Checker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bitwize-music-studio/claude-ai-music-skills/tree/main/skills/plagiarism-checker. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plagiarism Checker?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Plagiarism Checker?

As many as you like. As long as a model supports skills, you can use Plagiarism Checker with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Plagiarism Checker AI skill free?

Yes. It is published on GitHub by bitwize-music-studio under the CC0-1.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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