Soak Test
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add Donchitos/Claude-Code-Game-Studios --skill soak-testCompatible with
Supported agents
description: "Generate a soak test protocol for extended play sessions. Defines what to observe, measure, and log during long play sessions to surface slow leaks, fatigue effects, and edge cases that
argument-hint: "[duration: 30m | 1h | 2h | 4h] [focus: memory | stability | balance | all]"
allowed-tools: Read, Glob, Grep, Write
| name | soak-test |
| description | "Generate a soak test protocol for extended play sessions. Defines what to observe, measure, and log during long play sessions to surface slow leaks, fatigue effects, and edge cases that only appear after sustained play. Primarily used in Polish and Release phases." |
| argument-hint | "[duration: 30m | 1h | 2h | 4h] [focus: memory | stability | balance | all]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Write |
A soak test (also called an endurance test) is an extended play session run with specific observation goals. Unlike a smoke check (broad critical path, ~10 min) or a single-feature playtest (~30 min), a soak test runs for 30 minutes to several hours to surface:
This skill generates the observation protocol and analysis harness — the human does the actual playing.
Output: production/qa/soak-test-[date]-[duration].md
When to run:
/gate-check releaseDuration (default: 1h):
30m — short soak; suitable for testing a single mechanic or scene1h — standard soak; covers most common leak categories2h — extended soak; recommended for first full Polish soak4h — deep soak; required for games with long session design (RPGs, sims)Focus (default: all):
memory — focus on heap size, object count, leak patternsstability — focus on crash/freeze/hang detectionbalance — focus on fun fatigue, content exhaustion, difficulty perceptionall — all of the aboveRead:
.claude/docs/technical-preferences.md — engine (for engine-specific memory
monitoring guidance), performance budgets (memory ceiling, target FPS)design/gdd/game-concept.md — intended session length (for comparison against
soak duration), core loop descriptionproduction/playtests/ — prior playtest findings
(to avoid re-documenting known issues)production/qa/qa-plan-*.md — current sprint test coverage
(to understand what has been formally tested vs. what the soak covers)Note any performance budget targets from technical-preferences.md:
Based on duration, generate timed checkpoints:
30m soak: T+0, T+10, T+20, T+30 1h soak: T+0, T+15, T+30, T+45, T+60 2h soak: T+0, T+20, T+40, T+60, T+80, T+100, T+120 4h soak: T+0, T+30, T+60, T+90, T+120, T+180, T+240
At each checkpoint, the observer records the observation items defined in Phase 4.
Engine-specific monitoring guidance:
Godot 4:
Memory → Static Memory and
Object Count → Objects across checkpointsPerformance.get_monitor(Performance.MEMORY_STATIC) returns bytes
in Godot 4.6Unity:
Unreal Engine:
stat memory console command at each checkpointAt each checkpoint, note:
Collect subjective observations at each checkpoint:
# Soak Test Protocol
> **Date**: [date]
> **Duration**: [duration]
> **Focus**: [memory | stability | balance | all]
> **Engine**: [engine]
> **Generated by**: /soak-test
---
## Pre-Session Setup
Before starting the soak:
- [ ] Game is running from a **fresh launch** (not resumed from a prior session)
- [ ] All background applications closed (minimise OS memory interference)
- [ ] Performance monitoring tool open and recording:
- **Godot**: Debugger → Monitors tab → Memory section visible
- **Unity**: Memory Profiler window open
- **Unreal**: `stat memory` ready in console
- [ ] Soak target confirmed: [session design intent from game concept]
- [ ] Prior known issues to watch for: [from most recent playtest / qa-plan]
---
## Baseline (T+0) — Record Before Playing
| Metric | Baseline Value |
|--------|---------------|
| Memory / Heap | [record before first frame of gameplay] |
| Object Count | [record] |
| FPS (first 30 seconds) | [record] |
| [Engine-specific metric] | [record] |
---
## Checkpoint Log
### T+[N] minutes
**Memory / Stability** *(if applicable)*:
| Metric | Value | Δ from Baseline | Alert? |
|--------|-------|-----------------|--------|
| Memory / Heap | | | |
| Object Count | | | |
| FPS | | | |
| Crashes / Hangs | | | |
**Stability checks**:
- [ ] No crash or hang since last checkpoint
- [ ] Frame rate within budget ([N] fps target)
- [ ] Audio correct
- [ ] HUD rendering correctly
- [ ] Input responding correctly
**Balance / Fatigue** *(if applicable)*:
- Core mechanic still rewarding: Y / N
- Difficulty perception: too easy / appropriate / too hard
- Notable moments: [note any peak engagement or frustration]
- Content exhaustion signs: Y / N — [describe]
**Free observations**:
*(Note anything unexpected observed since the last checkpoint)*
---
[Repeat Checkpoint Log section for each timed checkpoint]
---
## Post-Session Analysis
### Memory Trend
| Checkpoint | Memory | Δ/hr extrapolated |
|------------|--------|-------------------|
| T+0 | | |
| [T+N] | | |
**Leak detected?** Y / N
**Estimated time to OOM at current rate**: [N hours / not applicable]
### Stability Summary
Total crashes: [N]
Total hangs: [N]
Worst FPS observed: [N] fps at [checkpoint]
Performance degradation: stable / mild / severe
### Balance / Fatigue Summary
Fun curve: [engaged throughout / fatigue onset at T+N / repetitive from start]
Content exhaustion point: [never / at T+N / early]
Difficulty arc: [appropriate / too easy throughout / difficulty spike at T+N]
### Issues Found
| ID | Severity | Checkpoint | Description |
|----|----------|------------|-------------|
| SOAK-001 | S[1-4] | T+[N] | [description] |
---
## Verdict: PASS / PASS WITH CONCERNS / FAIL
**PASS**: No leaks detected, stability maintained, fun factor consistent
**PASS WITH CONCERNS**: Minor drift or fatigue noted; addressable in Polish
**FAIL**: Memory leak confirmed, stability breach, or severe fun fatigue
---
## Sign-Off
- **Tester**: [name] — [date]
- **QA Lead review**: [name] — [date]
Present the protocol summary in conversation, then ask:
"May I write this soak test protocol to
production/qa/soak-test-[date]-[duration].md?"
Write only after approval.
After writing:
"Protocol written. To run the soak:
production/qa/bugs//bug-triage sprint after the session to integrate any S1/S2 issuesIf the verdict is FAIL, run /smoke-check again after fixing the issues."
all focus — narrow focus (memory-only) is for
regression soaks after a specific fix, not the first passAI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsoak-testExecute the skills CLI command in your project's root directory to begin installation:
epx add Donchitos/Claude-Code-Game-Studios --skill soak-testFetches soak-test from Donchitos/Claude-Code-Game-Studios and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/soak-test
Restart Cursor to activate soak-test. Access via /soak-testin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
gate-check
Donchitos/Claude-Code-Game-Studios · Game QA & Testing · same repo
create-architecture
Donchitos/Claude-Code-Game-Studios · Game Dev Planning · same repo
prototype
Donchitos/Claude-Code-Game-Studios · Game Dev Skills · same repo
help
Donchitos/Claude-Code-Game-Studios · Game Dev Planning · same repo
architecture-decision
Donchitos/Claude-Code-Game-Studios · Game Dev Planning · same repo
caveman-commit
JuliusBrussee/caveman · Marketing · 2 shared tags
soak-test fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
soak-test is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
soak-test reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: soak-test is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for soak-test matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in soak-test — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added soak-test from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend soak-test for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in soak-test — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend soak-test for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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