Datasets:

earakely-scale
/

MuseScoreFromRequestComputerEnv-REA

---
license: apache-2.0
pretty_name: MuseScore 3 computer-use environment from a one-line request (REA)
tags:
- computer-use
- cua
- gui-agent
- rl-environment
- agentenv
- desktop
- linux
- rea
- music
- music-notation
- score
- from-request
---
# MuseScore 3: a computer-use environment built from a one-line request

![An agent solving the task in MuseScore 3](media/hero.gif)

**The real MuseScore 3.2 music notation editor running on an Ubuntu 24.04 desktop, as an [agentenv](https://pypi.org/project/agentenv-framework/) computer environment. An agent completes the task only through screenshots, mouse and keyboard, and a verifier grades the saved files with no model.**

Claude Code built this environment from a one-line request in about 32 minutes, with only REA's build skill and MCP tools; [How it was made](#how-it-was-made) has the request and the steps. MuseScore opens a four-bar practice piece, `Documents/MuseScore3/Scores/Morning_Song.mscz`, at launch, behind its first-run Startup Wizard and Tour. The agent has to change the title shown on the score from Morning Song to Evening Lullaby and the composer from Theo Ashby to Clara Hollis, and save. It sees only the screen and acts only with the mouse and keyboard.

## Watch

- Agent runs (Claude Code with Claude Sonnet 5.5): [run 1](media/solve-1.mp4), [run 2](media/solve-2.mp4), [run 3](media/solve-3.mp4)
- Witness, which proves the task can be done through the computer: [witness.mp4](media/witness.mp4)

Each video is the computer's own screen recording at 10 frames per second.

## The task

> In MuseScore, change the title of the score in Documents/MuseScore3/Scores/Morning_Song.mscz to Evening Lullaby and its composer to Clara Hollis, then save it.
`bundle/artifacts/retitle-score-check/verify.py` reads the app's files through the computer's `data/get` view and passes only if every check holds:
| Check | Kind | File |
| --- | --- | --- |
| `title` | `text_contains` | `Documents/MuseScore3/Scores/Morning_Song.mscz` |
| `composer` | `text_contains` | `Documents/MuseScore3/Scores/Morning_Song.mscz` |
| `title-frame` | `text_equals` | `Documents/MuseScore3/Scores/Morning_Song.mscz` |
An `.mscz` file is a zip holding the score as `.mscx` XML, and REA reads the entry inside the zip. The title and composer are `Text` elements in the score's title frame (`VBox`), which have no attributes to select by, so the checks read the frame's whole text: it must contain "Evening Lullaby" and "Clara Hollis", and equal "10TitleEvening LullabySubtitlePractice piece in C majorComposerClara Hollis" exactly, the frame's height and each line's style and text run together. The exact match also proves the subtitle is untouched and nothing was added. Changing only the title in File > Score Properties leaves the title frame alone and fails.
## Results
3 of 3 runs passed, about $0.86 per run.
| Run | Outcome | Turns | Cost | Video |
| --- | --- | --- | --- | --- |
| 1 | passed | 17 | $1.12 | [video](media/solve-1.mp4) |
| 2 | passed | 18 | $0.87 | [video](media/solve-2.mp4) |
| 3 | passed | 18 | $0.58 | [video](media/solve-3.mp4) |
## Run it
You need Docker. `agentenv-framework` builds the computer: Ubuntu 24.04 with the app installed from Ubuntu's archive (`musescore3` 3.2.3).
```bash
pip install agentenv-framework==0.9.1431
hf download earakely-scale/MuseScoreFromRequestComputerEnv-REA --repo-type dataset --local-dir musescore-request
agent-env run musescore-request/bundle --task retitle-score --agent claude-code --model <model>
```
The agent needs a model provider configured for agentenv. `--task smoke` only boots the computer, with no agent. `bundle/README.md` describes the bundle in detail.
## How it was made
Claude Code built this environment from a one-line request, given only [REA](https://github.com/morluto/rea)'s build skill and REA's MCP tools:
> Build me a MuseScore environment where the agent changes the title and composer of a short score and saves it.
It asked only the skill's upfront questions, wrote no app-specific scripts, and finished in about 32 minutes.
It took a second capture. On the first, REA did not count the score as MuseScore's document: MuseScore's window title shows the score's title rather than its file name, so the export refused a check on the score. Claude Code started the second capture with the score's path as MuseScore's launch argument, saved the seed at that path, and the export accepted it. The steps were REA's usual ones:
1. **Capture.** REA launched MuseScore 3 on a Linux desktop and recorded its package, windows and opened files while the edit was made. It also recorded the app's state folders before and after.
2. **Export.** REA turned the capture into an agentenv `computer_app`. It installs the app, seeds the starting files, starts the app, and waits for its main window. It also serves typed views of the app's files for verifiers.
3. **Task.** The task's checks were validated against the capture: they fail on the starting state and pass on the captured end state.
4. **Witness.** In a fresh computer, the edit was made through computer actions alone, after dismissing the Startup Wizard and Tour, and the checks were read at four stages. They held on the first try:

| Stage | Checks |
| --- | --- |
| `seed` | fail, as expected |
| `after_edit` | pass |
| `near_miss` | fail, as expected: the composer was retyped as "Clara Hollins" |
| `after_reset` | fail, as expected: `data/reset` restored the seed |

The agent runs came after the build: Claude Code with Claude Sonnet 5.5 (`--model anthropic/claude-sonnet-5-5 --no-emulate`, on an amd64 host) solved the task 3 times, each run recorded.

## What's inside

```
bundle/      the agentenv bundle: envs/ (app module, seed files), tasks/, artifacts/ (verifier), evals/
media/       witness and agent-run recordings (MP4) with short GIF previews
results.json the runs above, with each check's result
```

## Limits

- MuseScore's settings are not part of the seed, so every boot shows its five-page Startup Wizard and then a Tour dialog, which the agent has to dismiss. After `data/reset`, MuseScore also asks whether to restore the previous session.
- The exact `title-frame` check fails if the agent adds or restyles a line in the title frame, even when the title and composer read correctly.
- The environment is named `mscore3`, after the program the `musescore3` package installs, so its files are under `bundle/envs/mscore3/`.
- The computer installs whatever `musescore3` Ubuntu 24.04's archive holds at build time (3.2.3 for these runs); it is not pinned.
- Three runs is a small sample: the solve rate shows the task is solvable, not how hard it is.

## Licences

The bundle code, the task and the synthetic seed files are Apache-2.0. MuseScore 3 itself is not included: the computer installs it from Ubuntu's archive (`musescore3` 3.2.3) at build time, under its own licence (GPL-2.0 with MuseScore's font exception).

	---
	license: apache-2.0
	pretty_name: MuseScore 3 computer-use environment from a one-line request (REA)
	tags:
	- computer-use
	- cua
	- gui-agent
	- rl-environment
	- agentenv
	- desktop
	- linux
	- rea
	- music
	- music-notation
	- score
	- from-request
	---

	# MuseScore 3: a computer-use environment built from a one-line request

	![An agent solving the task in MuseScore 3](media/hero.gif)

	The real MuseScore 3.2 music notation editor running on an Ubuntu 24.04 desktop, as an [agentenv](https://pypi.org/project/agentenv-framework/) computer environment. An agent completes the task only through screenshots, mouse and keyboard, and a verifier grades the saved files with no model.

	Claude Code built this environment from a one-line request in about 32 minutes, with only REA's build skill and MCP tools; [How it was made](#how-it-was-made) has the request and the steps. MuseScore opens a four-bar practice piece, `Documents/MuseScore3/Scores/Morning_Song.mscz`, at launch, behind its first-run Startup Wizard and Tour. The agent has to change the title shown on the score from Morning Song to Evening Lullaby and the composer from Theo Ashby to Clara Hollis, and save. It sees only the screen and acts only with the mouse and keyboard.

	## Watch

	- Agent runs (Claude Code with Claude Sonnet 5.5): [run 1](media/solve-1.mp4), [run 2](media/solve-2.mp4), [run 3](media/solve-3.mp4)
	- Witness, which proves the task can be done through the computer: [witness.mp4](media/witness.mp4)

	Each video is the computer's own screen recording at 10 frames per second.

	## The task

	> In MuseScore, change the title of the score in Documents/MuseScore3/Scores/Morning_Song.mscz to Evening Lullaby and its composer to Clara Hollis, then save it.

	`bundle/artifacts/retitle-score-check/verify.py` reads the app's files through the computer's `data/get` view and passes only if every check holds:

	\| Check \| Kind \| File \|
	\| --- \| --- \| --- \|
	\| `title` \| `text_contains` \| `Documents/MuseScore3/Scores/Morning_Song.mscz` \|
	\| `composer` \| `text_contains` \| `Documents/MuseScore3/Scores/Morning_Song.mscz` \|
	\| `title-frame` \| `text_equals` \| `Documents/MuseScore3/Scores/Morning_Song.mscz` \|

	An `.mscz` file is a zip holding the score as `.mscx` XML, and REA reads the entry inside the zip. The title and composer are `Text` elements in the score's title frame (`VBox`), which have no attributes to select by, so the checks read the frame's whole text: it must contain "Evening Lullaby" and "Clara Hollis", and equal "10TitleEvening LullabySubtitlePractice piece in C majorComposerClara Hollis" exactly, the frame's height and each line's style and text run together. The exact match also proves the subtitle is untouched and nothing was added. Changing only the title in File > Score Properties leaves the title frame alone and fails.

	## Results

	3 of 3 runs passed, about $0.86 per run.

	\| Run \| Outcome \| Turns \| Cost \| Video \|
	\| --- \| --- \| --- \| --- \| --- \|
	\| 1 \| passed \| 17 \| $1.12 \| [video](media/solve-1.mp4) \|
	\| 2 \| passed \| 18 \| $0.87 \| [video](media/solve-2.mp4) \|
	\| 3 \| passed \| 18 \| $0.58 \| [video](media/solve-3.mp4) \|

	## Run it

	You need Docker. `agentenv-framework` builds the computer: Ubuntu 24.04 with the app installed from Ubuntu's archive (`musescore3` 3.2.3).

	```bash
	pip install agentenv-framework==0.9.1431
	hf download earakely-scale/MuseScoreFromRequestComputerEnv-REA --repo-type dataset --local-dir musescore-request
	agent-env run musescore-request/bundle --task retitle-score --agent claude-code --model <model>
	```

	The agent needs a model provider configured for agentenv. `--task smoke` only boots the computer, with no agent. `bundle/README.md` describes the bundle in detail.

	## How it was made

	Claude Code built this environment from a one-line request, given only [REA](https://github.com/morluto/rea)'s build skill and REA's MCP tools:

	> Build me a MuseScore environment where the agent changes the title and composer of a short score and saves it.

	It asked only the skill's upfront questions, wrote no app-specific scripts, and finished in about 32 minutes.

	It took a second capture. On the first, REA did not count the score as MuseScore's document: MuseScore's window title shows the score's title rather than its file name, so the export refused a check on the score. Claude Code started the second capture with the score's path as MuseScore's launch argument, saved the seed at that path, and the export accepted it. The steps were REA's usual ones:

	1. Capture. REA launched MuseScore 3 on a Linux desktop and recorded its package, windows and opened files while the edit was made. It also recorded the app's state folders before and after.
	2. Export. REA turned the capture into an agentenv `computer_app`. It installs the app, seeds the starting files, starts the app, and waits for its main window. It also serves typed views of the app's files for verifiers.
	3. Task. The task's checks were validated against the capture: they fail on the starting state and pass on the captured end state.
	4. Witness. In a fresh computer, the edit was made through computer actions alone, after dismissing the Startup Wizard and Tour, and the checks were read at four stages. They held on the first try:

	\| Stage \| Checks \|
	\| --- \| --- \|
	\| `seed` \| fail, as expected \|
	\| `after_edit` \| pass \|
	\| `near_miss` \| fail, as expected: the composer was retyped as "Clara Hollins" \|
	\| `after_reset` \| fail, as expected: `data/reset` restored the seed \|

	The agent runs came after the build: Claude Code with Claude Sonnet 5.5 (`--model anthropic/claude-sonnet-5-5 --no-emulate`, on an amd64 host) solved the task 3 times, each run recorded.

	## What's inside

	```
	bundle/ the agentenv bundle: envs/ (app module, seed files), tasks/, artifacts/ (verifier), evals/
	media/ witness and agent-run recordings (MP4) with short GIF previews
	results.json the runs above, with each check's result
	```

	## Limits

	- MuseScore's settings are not part of the seed, so every boot shows its five-page Startup Wizard and then a Tour dialog, which the agent has to dismiss. After `data/reset`, MuseScore also asks whether to restore the previous session.
	- The exact `title-frame` check fails if the agent adds or restyles a line in the title frame, even when the title and composer read correctly.
	- The environment is named `mscore3`, after the program the `musescore3` package installs, so its files are under `bundle/envs/mscore3/`.
	- The computer installs whatever `musescore3` Ubuntu 24.04's archive holds at build time (3.2.3 for these runs); it is not pinned.
	- Three runs is a small sample: the solve rate shows the task is solvable, not how hard it is.

	## Licences

	The bundle code, the task and the synthetic seed files are Apache-2.0. MuseScore 3 itself is not included: the computer installs it from Ubuntu's archive (`musescore3` 3.2.3) at build time, under its own licence (GPL-2.0 with MuseScore's font exception).