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 zenstory-ai/novel-to-game --skill game-qagit clone --depth 1 https://github.com/zenstory-ai/novel-to-gameWrote 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/zenstory-ai/novel-to-game/game-qa)<a href="https://agentmods.dev/skills/zenstory-ai/novel-to-game/game-qa"><img src="https://agentmods.dev/badge/skills/zenstory-ai/novel-to-game/game-qa/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/zenstory-ai/novel-to-game/game-qa"><img src="https://agentmods.dev/badge/skills/zenstory-ai/novel-to-game/game-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00146 | $0.00725 |
| Opus 5 | $0.00073 | $0.00362 |
| Sonnet 5 | $0.00029 | $0.00145 |
| Haiku 4.5 | $0.00015 | $0.00072 |
Grade A, and why
game-qa 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 4d 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
1 near-identical copy found in the catalogue:
- game-qa — 100% identical, 7 lines differ
What it actually says
游戏质量验证
验证当前候选能否完成最小可玩闭环，不把自动化结果包装成趣味、平衡、权利或发布质量结论。
读取 qa-contract.md 定判据，按 test-design-method.md 设计最少但有区分力的检查。
产物语言由 PRODUCT_BRIEF.md 锁定；未锁定时跟随对话语言，不默认产出中文。
唯一必需合同
每个候选都必须用真实运行证据覆盖：launch、render、input、coreLoop、outcome、restart。
targetFinish 描述成色，不改变这组六项，也不得生成第七道门。
执行
- 读取
targetRuntime、testedRuntime和权威 verify；与 PRODUCT_BRIEF/BUILD_BRIEF 冲突时先报错， 不由 QA 猜值。 - 运行权威 verify：它在 testedRuntime 从 clean start → 核心动作 → 设计结果 → restart 完成整条路径，并记录 command、exit code、环境、六项结果、最小证据和实际失败。
- 对照 GAME_DESIGN 中会改变结果的不变量和结束标记；只验证批准的设计承诺，不遍历所有 代码路径。
- 若候选有可执行模型、事件日志、patch 或
signature_command，按 test-design-method 的对应合同把 项目回归嵌入权威 verify；允许定向诊断、修复和复跑，最终六项证据必须来自同一次完整运行。 失败映射到已有 checks 或 limitation，不新增通用门禁，不拼接不同运行的 PASS。 - 记录 limitation 和问题的 product/design/art/build 归属。趣味、长期平衡、留存和商业价值只能写成 未验证风险，不给确定性 PASS。
优先使用已有可观察状态；只有无法判断结果时才增加最小测试钩子。不要为了 QA 重构游戏或强制某种 框架、测试库或调试接口。
输出
qa/verification.json：唯一 QA 事实源，包含三态 status、权威命令、complete run、六项 checks、 一条证据路径和 limitations；字段与证据要求见 qa-contract.md。
缺口写结构化 limitation，不发明 PASS_WITH_GAPS；未运行或失败的必需项不能满足整体 PASS。
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed · +1 lines ddb75ad7c94f
- 7d ago Changed · -10 lines 5f76bc51fe89
- 13d ago First seen · 51 lines · 146 tokens per session scan A 6835e17fcdec
game-qa is a skill published in the GitHub repository zenstory-ai/novel-to-game (775 stars, last pushed yesterday), licensed MIT. It adds 146 tokens to every session and 725 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
prototype
Concept prototype — validate the core idea is worth designing before writing GDDs. Run right after /brainstorm and /setup-engine. Routes to HTML, Engine, or Paper path based on game type. Produces a throwaway build and a PROCEED/PIVOT/KILL verdict.
dev-story
Read a story file and implement it. Loads the full context (story, GDD requirement, ADR guidelines, control manifest), routes to the right programmer agent for the system and engine, implements the code and test, and confirms each acceptance criterion. The core implementation skill — run after /story-readiness, before…
smoke-check
Run the critical path smoke test gate before QA hand-off. Executes the automated test suite, verifies core functionality, and produces a PASS/FAIL report. Run after a sprint's stories are implemented and before manual QA begins. A failed smoke check means the build is not ready for QA.
test-helpers
Generate engine-specific test helper libraries for the project's test suite. Reads existing test patterns and produces tests/helpers/ with assertion utilities, factory functions, and mock objects tailored to the project's systems. Reduces boilerplate in new test files.
regression-suite
Map test coverage to GDD critical paths, identify fixed bugs without regression tests, flag coverage drift from new features, and maintain tests/regression-suite.md. Run after implementing a bug fix or before a release gate.
soak-test
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.