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kiri603/To-Sheet-Music-Skill
Automatically transforms mixed song recordings into playable five-piece school band arrangements through audio separation, music transcription, arrangement, and difficulty adjustment. Outputs include MIDI, print-ready PDF scores, and editable MuseScore (.mscz) files.将混音歌曲音频自动分轨、扒谱并改编为适合五人校园乐队演奏的伴奏总谱,支持难度调整,并输出 MIDI、PDF 总谱和可编辑的 MuseScore(.mscz)文件。
History
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Heat
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Individual skills in this repository
How it works
audio-to-band-score
When your agent uses it
将用户提供的混音歌曲音频自动分轨、扒谱并改编为可演奏的五件校园乐队伴奏总谱,交付 MIDI、PDF 和可编辑 MSCZ。用于音频到乐队谱、歌曲扒带、乐队改编与难度调整;不用于语音转写、歌词翻译或仅下载现成曲谱。
What it loads into context
Frontmatter
92 tokensAlways available to the agent
SKILL.md
3,399 tokensWhen the skill is activated
Reference documents
19,397 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 默认约定
- 开始执行
- 分轨与音频证据
- 扒谱与可演奏编配
- 谱面与三个导出文件
- 执行效率
- 内部修正与交付
Scripts executed separately
scripts/benchmark_playability.pyscripts/fidelity_audit.pyscripts/rhythm_audit.pyscripts/score_events.pyscripts/score_tools.pyscripts/separate_audio.pyscripts/test_fidelity_audit.pyscripts/test_native_dead.pyscripts/test_notation_features.pyscripts/test_playability.pyscripts/test_rhythm_audit.pyscripts/test_score_events.pyscripts/test_score_tools.pyscripts/test_separate_audio.pyscripts/test_transcription_evidence.pyscripts/transcription_evidence.py
Files
.github/workflows/tests.ymlasset753 bytes.gitignoreasset371 bytesLICENSEasset1,064 bytesREADME.mddoc13,929 bytesSKILL.mdcore12,467 bytesagents/openai.yamlasset345 bytesassets/band-style.mssasset686 bytesassets/band-template.mscxasset21,247 bytesassets/score-previews/beyond.pngasset98,156 bytesassets/score-previews/haruhikage.pngasset52,522 bytesassets/score-previews/koe.pngasset47,438 bytesassets/score-previews/zattou-bokura-no-machi.pngasset54,749 bytesreferences/arranging.mddoc13,579 bytesreferences/notation-and-qa.mddoc11,824 bytesreferences/score-events.mddoc10,504 bytesreferences/separation.mddoc5,134 bytesreferences/toolchain.mddoc5,220 bytesreferences/transcription-fidelity.mddoc9,617 bytesscripts/benchmark_playability.pyruns2,111 bytesscripts/fidelity_audit.pyruns13,497 bytesscripts/rhythm_audit.pyruns9,621 bytesscripts/score_events.pyruns84,157 bytesscripts/score_tools.pyruns25,344 bytesscripts/separate_audio.pyruns10,776 bytesscripts/test_fidelity_audit.pyruns13,045 bytesscripts/test_native_dead.pyruns1,670 bytesscripts/test_notation_features.pyruns3,071 bytesscripts/test_playability.pyruns12,995 bytesscripts/test_rhythm_audit.pyruns5,532 bytesscripts/test_score_events.pyruns15,520 bytesscripts/test_score_tools.pyruns14,783 bytesscripts/test_separate_audio.pyruns2,598 bytesscripts/test_transcription_evidence.pyruns2,655 bytesscripts/transcription_evidence.pyruns9,388 bytes
Read SKILL.md
# 音频转校园乐队总谱
你是负责交付成品的音乐编配 agent。目标是让乐队拿到结构完整、节奏清楚、符合实际演奏条件的伴奏总谱。执行音频分析、编配、校验与导出,不以工作流说明或未经整理的识别 MIDI 代替交付。
## 默认约定
- 用户提供混音完成的歌曲音频和要求。已有信息直接沿用;仅缺少实际音频、关键指定版本或不可推断的硬约束时询问。
- 五件乐器为歌手伴奏:主音吉他、节奏吉他、贝斯、键盘、鼓。人声用于分析结构与避让,不默认让吉他或键盘持续代唱。
- 默认校园乐队业余中级;支持整队、单声部的难度、调弦、调性、变调夹、曲长等自定义要求。用户当前要求优先于默认值。
- 可演奏性优先,同时保留原曲的和声走向、节奏重心、段落层次、标志性 riff、前奏和间奏。允许简化或重新分配声部,不能用通用和弦循环替换整首实际内容。
- 全程使用免费工具和模型。本地执行优先;不依赖付费 API、收费音色、订阅、试用额度或需要支付信息的服务。无需额外购买任何插件。普通开源工具安装和模型下载仍遵守运行环境已有权限。
- 固定交付三个文件:`歌曲名_band.mid`、`歌曲名_band.pdf`、`歌曲名_band.mscz`。MusicXML、分析记录、分离音轨和试听文件保留在工作目录;只有用户需要时再作为额外交付。
## 开始执行View the complete source on GitHubSkills included
- audio-to-band-score
Repository facts
- License
- MIT
- Created
- Sep 8, 2026
- Last pushed
- Sep 17, 2026
- Forks
- 17
- Open issues
- 1
- Project activity
- Active
Before you install
Local scriptsAutomated signals, not a guarantee
Checked Nov 6, 2026
- No broad tool permissions
- No dangerous shell commands
- 31 network referencesin 6 files: README.md:7 references/toolchain.md:55 references/notation-and-qa.md:95 and 3 more
- No hidden or obfuscated text
- No instruction overrides
- 16 executable scriptsin 16 files: scripts/benchmark_playability.py:1 scripts/fidelity_audit.py:1 scripts/rhythm_audit.py:1 and 13 more
- 2 references to secretsin 2 files: scripts/score_tools.py:340 scripts/separate_audio.py:207
- No requests to vote in Hot
Show all 49 signals by file
README.md
- Network accessline 7
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[](https://github.com/kiri603/To-Sheet-Music-Skill/actions/workflows/tests.yml) - Network accessline 14
本项目认可并支持 [LINUX DO 社区](https://linux.do/)。 - Network accessline 51
[▶ Watch the project introduction on Bilibili](https://www.bilibili.com/video/BV176b56VEN3/?vd_source=2620b2603c03718cf25e33b2e0d30995#reply117234387130258) - Network accessline 118
git clone https://github.com/kiri603/To-Sheet-Music-Skill.git - Network accessline 264
- [Demucs](https://github.com/adefossez/demucs) for music source separation. - Network accessline 265
- [Basic Pitch](https://github.com/spotify/basic-pitch) for optional single-instrument note candidates. - Network accessline 266
- [librosa](https://librosa.org/) for optional audio and beat analysis. - Network accessline 267
- [MuseScore Studio](https://musescore.org/) for notation, score editing, and export. - Network accessline 268
- [MusicXML](https://www.w3.org/2021/06/musicxml40/) for interoperable notation data. - Network accessline 280
<a href="https://www.star-history.com/?repos=kiri603%2Fto-sheet-music-skill&type=date&legend=top-left"> - Network accessline 281
<picture> <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=kiri603/to-sheet-music-skill&type=date&theme=dark&legend=top-left" /> <source media="(prefers-color-scheme: light)" srcset="https: - Network accessline 282
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=kiri603/to-sheet-music-skill&type=date&theme=dark&legend=top-left" /> - Network accessline 283
<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=kiri603/to-sheet-music-skill&type=date&legend=top-left" /> - Network accessline 284
<img alt="Star History Chart" src="https://api.star-history.com/chart?repos=kiri603/to-sheet-music-skill&type=date&legend=top-left" />
references/notation-and-qa.md
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- [librosa pYIN](https://librosa.org/doc/0.11.0/generated/librosa.pyin.html):输出基频、有声标志及有声概率;不是起音或静音的真值。 - Network accessline 96
- [librosa onset detection](https://librosa.org/doc/0.11.0/generated/librosa.onset.onset_detect.html):从起音强度峰取得候选;空检测不证明真实静音。 - Network accessline 97
- [MusicXML string](https://www.w3.org/2021/06/musicxml40/musicxml-reference/elements/string/) - Network accessline 98
- [MusicXML staff-tuning](https://www.w3.org/2021/06/musicxml40/musicxml-reference/elements/staff-tuning/)
references/score-events.md
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方法参考:[From MIDI to Rich Tablatures](https://arxiv.org/html/2407.09052v1),本实现只采用弦品候选、手把位状态和路径代价的基本思路。 - Network accessline 85
格式依据:[MusicXML note 顺序及延音](https://www.w3.org/2021/06/musicxml40/musicxml-reference/elements/note/)、[midi-unpitched 的 1..128 编号](https://www.w3.org/2021/06/musicxml40/musicxml-reference/elements/midi-unpitched/)。
references/separation.md
references/toolchain.md
- Network accessline 55
- [Demucs](https://github.com/adefossez/demucs):分离模型、许可、安装与 API。 - Network accessline 56
- [Basic Pitch](https://github.com/spotify/basic-pitch):单乐器适用范围、CLI 与 Python 兼容说明。 - Network accessline 57
- [librosa 节拍检测](https://librosa.org/doc/0.11.0/beat.html):节拍候选接口;仍需处理半速、倍速和弱起。 - Network accessline 58
- [MuseScore 命令行](https://musescore.org/en/print/book/export/html/329750):转换参数;该页包含沿用的旧版内容,实际本机输出仍须验证。 - Network accessline 59
- [MuseScore 文件导出](https://handbook.musescore.org/en_gb/file-management/file-export):原生和交换文件格式。 - Network accessline 60
- [MusicXML TAB](https://www.w3.org/2021/06/musicxml40/tutorial/tablature/):弦、品、节奏与调弦表示。
references/transcription-fidelity.md
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轨名只是模型估计类别。[Demucs](https://github.com/facebookresearch/demucs) 将六源模型列为实验性,钢琴分离尤其有限;[Basic Pitch](https://github.com/spotify/basic-pitch) 对单一乐器更有效。这些是排查方向,具体原因仍须用当前歌曲片段查证。
scripts/benchmark_playability.py
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scripts/fidelity_audit.py
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scripts/rhythm_audit.py
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scripts/score_events.py
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scripts/score_tools.py
scripts/separate_audio.py
scripts/test_fidelity_audit.py
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scripts/test_native_dead.py
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scripts/test_notation_features.py
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scripts/test_playability.py
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scripts/test_rhythm_audit.py
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scripts/test_score_events.py
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scripts/test_score_tools.py
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scripts/test_separate_audio.py
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scripts/test_transcription_evidence.py
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scripts/transcription_evidence.py
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How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Signal confidence: 49 facts
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- Network access in prose of documentationreferences/transcription-fidelity.md:17Low confidence
- Executable script in prose of a file that runsscripts/benchmark_playability.py:1Low confidence
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- Executable script in prose of a file that runsscripts/score_events.py:1Low confidence
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- Access to secrets in code of a file that runs: a variable, placeholder or call, not a stored valuescripts/score_tools.py:340Low confidence
- Executable script in prose of a file that runsscripts/separate_audio.py:1Low confidence
- Access to secrets in code of a file that runs: a variable, placeholder or call, not a stored valuescripts/separate_audio.py:207Low confidence
- Executable script in prose of a testscripts/test_fidelity_audit.py:1Low confidence
- Executable script in code of a testscripts/test_native_dead.py:1Low confidence
- Executable script in code of a testscripts/test_notation_features.py:1Low confidence
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Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.