SentryKnown publishergetsentry/sentry-unreal/.claude/skills/ue-unit-test/SKILL.md

ue-unit-test

Skill176 starsChanged 4 months agoMITView on GitHub

Run Sentry unit tests via Unreal automation

In this repository5 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- build-depsSkill
- packSkill
- ue-buildSkill
- ue-integration-testSkill

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Distinctive:
Run Sentry unit tests via Unreal Engine automation framework.
line 6
Very specific:
Check the UNREAL_ENGINE_ROOT environment variable (use PowerShell .NET method on Windows: …
line 10
Very specific:
If the report is missing or the run crashed, check sample/Saved/Logs/ for the root cause.
line 57

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

Run Sentry unit tests via Unreal Engine automation framework.

Prerequisite: the project must be built first (a compile-only editor build is sufficient). If unsure whether it's been built, ask the user. If not built, suggest running /ue-build first.

Check the UNREAL_ENGINE_ROOT environment variable (use PowerShell .NET method on Windows: [System.Environment]::GetEnvironmentVariable('UNREAL_ENGINE_ROOT')). If unset or the path doesn't exist, ask the user for the engine path.
Determine the engine version by reading the EngineAssociation field in sample/SentryPlayground.uproject (e.g., "EngineAssociation": "5.7" - UE5, "EngineAssociation": "4.27" - UE4). Select the headless editor binary based on host OS and engine version:

Host OS	UE5 binary path	UE4 binary path
Windows	`Engine/Binaries/Win64/UnrealEditor-Cmd.exe`	`Engine/Binaries/Win64/UE4Editor-Cmd.exe`
macOS	`Engine/Binaries/Mac/UnrealEditor-Cmd`	`Engine/Binaries/Mac/UE4Editor-Cmd`
Linux	`Engine/Binaries/Linux/UnrealEditor-Cmd`	`Engine/Binaries/Linux/UE4Editor-Cmd`

Resolve the repo root and run the automation command:

REPO=$(git rev-parse --show-toplevel)

# Windows UE5
"$UNREAL_ENGINE_ROOT/Engine/Binaries/Win64/UnrealEditor-Cmd.exe" \
    "$REPO/sample/SentryPlayground.uproject" \
    -ReportExportPath="$REPO/sample/Saved/Automation" \
    -ExecCmds="Automation RunTests Sentry;quit" \
    -TestExit="Automation Test Queue Empty" \
    -Unattended -NoPause -NoSplash -NullRHI

# macOS UE5
"$UNREAL_ENGINE_ROOT/Engine/Binaries/Mac/UnrealEditor-Cmd" \
    "$REPO/sample/SentryPlayground.uproject" \
    -ReportExportPath="$REPO/sample/Saved/Automation" \
    -ExecCmds="Automation RunTests Sentry;quit" \
    -TestExit="Automation Test Queue Empty" \
    -Unattended -NoPause -NoSplash -NullRHI

# Linux UE5
"$UNREAL_ENGINE_ROOT/Engine/Binaries/Linux/UnrealEditor-Cmd" \
    "$REPO/sample/SentryPlayground.uproject" \
    -ReportExportPath="$REPO/sample/Saved/Automation" \
    -ExecCmds="Automation RunTests Sentry;quit" \
    -TestExit="Automation Test Queue Empty" \
    -Unattended -NoPause -NoSplash -NullRHI

The test run can take longer than the default command timeout — run it in the background and monitor its output, or raise the timeout accordingly.

Report the results. The editor's exit code is not a reliable pass/fail signal for automation runs — read the report at sample/Saved/Automation/index.json instead:
- Summarize the number of passed and failed tests (succeeded / failed counts).
- For each failed test, report its full name and the error messages from its report entries.
If the report is missing or the run crashed, check sample/Saved/Logs/ for the root cause.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

It worked
Partly
It didn't

What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free