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

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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.

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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