# MuseScore 3 computer app

Exported by REA's `export-desktop-application` from a capture of the `musescore3` package
(capture Evidence `ev_cde1fe73216a4e36661388fd18926eaf1ccbf6bb6a939bc7ba069a746caa6c88`). It was checked against agentenv-framework
0.9.1431.

- `envs/mscore3/` is a computer app on the `ubuntu-24.04` base with the `reference` driver, for
  `amd64` and `arm64`. It installs `musescore3` from the distribution archive, launches `sh -c cd "$HOME" 2>/dev/null; exec 'mscore3' "$HOME"/'Documents/MuseScore3/Scores/Morning_Song.mscz'` at boot and is ready
  when a window of class `MuseScore3` appears.
- Owned paths: `~/Documents/MuseScore3/Scores`.
  `data/get` returns their files and a typed JSON view of each; `data/reset` restores the seed.
- Seed: 1 file(s) made for the task, as saved at checkpoint `seed`.
  Text files and dconf keys spell the capture host's name as `localhost`, `user@host` as `user@localhost`
  and the home as `/home/user`, which the computer respells to its own at boot.
- `tasks/smoke.json` deploys the app.

Run the task with `agent-env run <this folder>`, or only the deploy with `--task smoke`.

The seed was made for this task, not taken from a user's own data; read `envs/mscore3/seed/` before publishing the bundle.

## Task `retitle-score`

`tasks/retitle-score.json` deploys the app, has the agent work through the computer from the prompt below, and grades
the outcome with `artifacts/retitle-score-check/verify.py`, which reads the app's `data/get` views and needs
no model. `evals/mscore3.toml` names it, so a run of the bundle runs it.

> 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.

Checks, each of which must pass:

- `title`: `{"kind":"text_contains","file":"Documents/MuseScore3/Scores/Morning_Song.mscz","pointer":"/entries/[name=Morning_Song.mscx]/view/root/children/[name=Score]/children/[name=Staff]/children/[name=VBox]","value":"Evening Lullaby"}`
- `composer`: `{"kind":"text_contains","file":"Documents/MuseScore3/Scores/Morning_Song.mscz","pointer":"/entries/[name=Morning_Song.mscx]/view/root/children/[name=Score]/children/[name=Staff]/children/[name=VBox]","value":"Clara Hollis"}`
- `title-frame`: `{"kind":"text_equals","file":"Documents/MuseScore3/Scores/Morning_Song.mscz","pointer":"/entries/[name=Morning_Song.mscx]/view/root/children/[name=Score]/children/[name=Staff]/children/[name=VBox]","value":"10TitleEvening LullabySubtitlePractice piece in C majorComposerClara Hollis"}`

REA kept the task because its checks fail on the seed (`title`, `composer`, `title-frame`) and all
pass on the captured end state.

To measure a solve rate, run the task k times (3 by default) with the agent and model to measure, and count the runs
whose summary line says `passed`; a run that says `failed` did not finish and is run again rather than counted:

    agent-env run <this folder> --task retitle-score --agent claude-code --model MODEL