plagiarism-checker

Files (1)

• SKILL.md

SKILL.md (first lines)

## 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

| Level | Criteria | Action |
|-------|----------|--------|
| **HIGH** | 5+ consecutive matching words from a known song, especially chorus/hook | Rewrite the line immediately |
| **MEDIUM** | 4-word match from known song, or structural similarity flagged by LLM | Review and consider rewording |
| **LOW** | Common phrasing overlap, likely coincidence | Note 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

| Verdict | Criteria |

From bitwize-music-studio/claude-ai-music-skills, CC0-1.0.

More from bitwize-music-studio/claude-ai-music-skills