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 qa-plangit 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/qa-plan)<a href="https://agentmods.dev/skills/donchitos/claude-code-game-studios/qa-plan"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/qa-plan/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/qa-plan"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/qa-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
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 →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 261 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- 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.
- medium Excessive Agency · line 268 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00073 | $0.02934 |
| Opus 5 | $0.00036 | $0.01467 |
| Sonnet 5 | $0.00015 | $0.00587 |
| Haiku 4.5 | $0.00007 | $0.00293 |
Grade C, and why
qa-plan scanned grade C with 1 finding 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 8d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- QA-PLAN: [date] | System: [system/sprint identifier] | Plan written: production/qa/qa-plan-[identifier]-[date].md --> Copies of this mod
1 near-identical copy found in the catalogue:
- qa-plan — 95% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Plan
This skill generates a structured QA plan for a sprint, feature, or individual story. It reads all in-scope story files and their referenced GDDs, classifies each story by test type, and produces a plan that tells developers exactly what to automate, what to verify manually, what the smoke test scope is, and when to bring in a playtester.
Run this before a sprint begins so the team knows upfront what testing work is required. A test plan written after implementation is a post-mortem, not a plan.
Output: production/qa/qa-plan-[sprint-slug]-[date].md
Phase 1: Parse Scope
Argument: $ARGUMENTS (blank = ask user via AskUserQuestion)
Determine scope from the argument:
sprint— read the most recent file inproduction/sprints/, extract every story file path referenced. Ifproduction/sprint-status.yamlexists, use it as the primary story list and fall back to the sprint plan for story metadata.feature: [system-name]— globproduction/epics/*/story-*.md, filter to stories whose file path or title contains the system name. Also check the epic index file (EPIC.md) in that system's directory.story: [path]— validate that the path exists and load that single file.- No argument — use
AskUserQuestion:- "What is the scope for this QA plan?"
- Options: "Current sprint", "Specific feature (enter system name)", "Specific story (enter path)", "Full epic"
After resolving scope, report: "Building QA plan for [N] stories in [scope]."
If a story file path is referenced but the file does not exist, note it as MISSING and continue with the remaining stories. Do not fail the entire plan for one missing file.
Phase 2: Load Inputs
For each in-scope story file, read the full file and extract:
- Story title and story ID (from filename or header)
- Story Type field (if present in the file header — e.g.,
Type: Logic) - Acceptance criteria — the complete numbered/bulleted list
- Implementation files — listed under "Files to Create / Modify" or similar
- Engine notes — any engine API warnings or version-specific notes
- GDD reference — the GDD path(s) cited
- ADR reference — the ADR(s) cited
- Estimate — hours or story points if present
- Dependencies — other stories this one depends on
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.
- 8d ago First seen · 279 lines · 73 tokens per session scan C f4e9823754aa
qa-plan is a skill published in the GitHub repository Donchitos/Claude-Code-Game-Studios (24,978 stars, last pushed 3mo ago), licensed MIT. It adds 73 tokens to every session and 2,934 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
game-qa
Verify a game with evidence on its selected target runtime. Launch the actual build and prove real rendering, input, the core loop, at least one designed outcome, restart, and explicit limitations without dressing subjective fun up as a certain verdict. Use for test a generated game, QA a game build, check whether the…
flame-harness-evaluator
Phase 6 — skeptical QA. Run the game, watch it, then judge against the contract. Default = functional check; --strict adds quality and edge-case passes.
unity-testing
Use when writing or structuring tests — EditMode vs PlayMode test decisions, test architecture, what to test in Unity, mocking strategies, and CI integration for Unity tests.
unity-tests-write
Use when writing Unity tests, including EditMode tests, PlayMode tests, performance testing, and code coverage.
forward-derivation
Derive BDD scenarios and TDD test skeletons from approved SDD specifications. ATDD acceptance test tables are optional output for specialized needs. Use when: spec is approved, starting BDD/TDD implementation, generating test structures. Keywords: forward derivation, spec to test, BDD generation, TDD skeleton, test…
atdd-assistant
A guide to Acceptance Test-Driven Development, or ATDD, a process where a team agrees on user-story requirements and acceptance tests before coding. Acceptance tests check whether a feature meets the agreed business requirements.