Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bitwize-music-studio/claude-ai-music-skills --skill plagiarism-checkergit clone --depth 1 https://github.com/bitwize-music-studio/claude-ai-music-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bitwize-music-studio/claude-ai-music-skills/plagiarism-checker)<a href="https://agentmods.dev/skills/bitwize-music-studio/claude-ai-music-skills/plagiarism-checker"><img src="https://agentmods.dev/badge/skills/bitwize-music-studio/claude-ai-music-skills/plagiarism-checker/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bitwize-music-studio/claude-ai-music-skills/plagiarism-checker"><img src="https://agentmods.dev/badge/skills/bitwize-music-studio/claude-ai-music-skills/plagiarism-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 5 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.01363 |
| Opus 5 | $0.00017 | $0.00681 |
| Sonnet 5 | $0.00007 | $0.00273 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
plagiarism-checker scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your Task
Target: $ARGUMENTS
- Get lyrics for the specified track(s)
- Extract distinctive phrases using MCP tool
- Web search top phrases for matches against known songs
- Use LLM knowledge to independently flag similarities
- 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_suggestionsreturned 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:
- WebFetch the lyrics page
- Compare the matching section against the user's lyrics
- 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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 169 lines · 35 tokens per session scan A d1959ebc72cd
plagiarism-checker is a skill published in the GitHub repository bitwize-music-studio/claude-ai-music-skills (483 stars, last pushed 2d ago), licensed CC0-1.0. It adds 35 tokens to every session and 1,363 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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