Claude Code Game Studios is a setup that organizes Claude Code into a coordinated game-development team of specialized AI agents. It supports game projects across design, programming, art, audio, narrative, quality assurance, and production, with skills and workflows for coordinating that work.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Donchitos/Claude-Code-Game-Studios --skill test-evidence-reviewgit clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-StudiosWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/donchitos/claude-code-game-studios/test-evidence-review)<a href="https://agentmods.dev/skills/donchitos/claude-code-game-studios/test-evidence-review"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/test-evidence-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/donchitos/claude-code-game-studios/test-evidence-review"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/test-evidence-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 7 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.02117 |
| Opus 5 | $0.00030 | $0.01059 |
| Sonnet 5 | $0.00012 | $0.00423 |
| Haiku 4.5 | $0.00006 | $0.00212 |
Grade A, and why
test-evidence-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- test-evidence-review — 100% identical, 1 lines differ
- test-evidence-review — 100% identical, 1 lines differ
- test-evidence-review — 94% identical, 40 lines differ
How it starts
The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Evidence Review
/smoke-check verifies that test files exist and pass. This skill
goes further — it reviews the quality of those tests and evidence documents.
A test file that exists and passes may still leave critical behaviour uncovered.
A manual evidence doc that exists may lack the sign-offs required for closure.
Output: Summary report (in conversation) + optional production/qa/evidence-review-[date].md
When to run:
- Before QA hand-off sign-off (
/team-qaPhase 5) - On any story where test quality is in question
- As part of milestone review for Logic and Integration story quality audit
1. Parse Arguments
Modes:
/test-evidence-review [story-path]— review a single story's evidence/test-evidence-review sprint— review all stories in the current sprint/test-evidence-review [system-name]— review all stories in an epic/system- No argument — ask which scope: "Single story", "Current sprint", "A system"
2. Load Stories in Scope
Based on the argument:
Single story: Read the story file directly. Extract: Story Type, Test Evidence section, story slug, system name.
Sprint: Read the most recently modified file in production/sprints/.
Extract the list of story file paths from the sprint plan. Read each story file.
System: Glob production/epics/[system-name]/story-*.md. Read each.
For each story, collect:
Type:field (Logic / Integration / Visual/Feel / UI / Config/Data)## Test Evidencesection — the stated expected test file path or evidence doc- Story slug (from file name)
- System name (from directory path)
- Acceptance Criteria list (all checkbox items)
3. Locate Evidence Files
For each story, find the evidence:
Logic stories: Glob tests/unit/[system]/[story-slug]_test.*
- If not found, also try: Grep in
tests/unit/[system]/for files containing the story slug
Integration stories: Glob tests/integration/[system]/[story-slug]_test.*
- Also check
production/session-logs/for playtest records mentioning the story
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 252 lines · 59 tokens per session scan A 04cdf0b7e94a
test-evidence-review is a skill published in the GitHub repository Donchitos/Claude-Code-Game-Studios (24,880 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 2,117 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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