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 pixel-cellar/Claude-Code-Game-Studios --skill team-audiogit clone --depth 1 https://github.com/pixel-cellar/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/pixel-cellar/claude-code-game-studios/team-audio)<a href="https://agentmods.dev/skills/pixel-cellar/claude-code-game-studios/team-audio"><img src="https://agentmods.dev/badge/skills/pixel-cellar/claude-code-game-studios/team-audio/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/pixel-cellar/claude-code-game-studios/team-audio"><img src="https://agentmods.dev/badge/skills/pixel-cellar/claude-code-game-studios/team-audio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00042 | $0.00950 |
| Opus 5.5 | $0.00017 | $0.00380 |
| Sonnet 5.5 | $0.00008 | $0.00190 |
| Haiku 4.5 | $0.00004 | $0.00095 |
Grade A, and why
team-audio 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 1mo 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.
What it actually says
当此技能被调用时,通过结构化管线编排音频团队。
决策点:在每个步骤转换时,使用 AskUserQuestion 将子代理的提案以可选项的形式呈现给用户。在对话中完整展示代理的分析内容,然后以简洁标签记录决策。用户必须批准后才能进入下一步。
-
读取参数,获取目标功能或区域(例如
combat、main menu、forest biome、boss encounter)。 -
收集上下文:
- 读取
design/gdd/中与该功能相关的设计文档 - 读取音频圣经
design/gdd/sound-bible.md(如存在) - 读取
assets/audio/中现有的音频资产列表 - 读取该区域已有的音效设计文档
- 读取
如何委派
使用 Task 工具将每个团队成员作为子代理(Subagent)生成:
subagent_type: audio-director— 声音标识、情感基调、音频调色板subagent_type: sound-designer— 音效规格、音频事件、混音分组subagent_type: technical-artist— 音频中间件、总线结构、内存预算subagent_type: gameplay-programmer— 音频管理器、游戏性触发器、自适应音乐
始终在每个代理的提示中提供完整上下文(功能描述、现有音频资产、设计文档引用)。
- 按顺序编排音频团队:
步骤 1:音频方向(audio-director)
生成 audio-director 代理以:
- 定义该功能/区域的声音标识
- 指定情感基调和音频调色板
- 设定音乐方向(自适应层级、分轨 Stems、过渡方式)
- 定义音频优先级和混音目标
- 建立自适应音频规则(战斗强度、探索、紧张感)
步骤 2:音效设计(sound-designer)
生成 sound-designer 代理以:
- 为每个音频事件创建详细的音效规格
- 定义声音类别(环境音、UI 音、游戏性音效、音乐、对白)
- 指定每个声音的参数(音量范围、音调变化、衰减曲线 Attenuation)
- 规划音频事件列表及触发条件
- 定义混音分组和闪避规则(Ducking Rules)
步骤 3:技术实现(technical-artist)
生成 technical-artist 代理以:
- 设计音频中间件集成方案(Wwise/FMOD/原生)
- 定义音频总线结构和路由
- 指定各平台音频资产的内存预算
- 规划流式加载(Streaming)与预加载资产策略
- 设计音频驱动的视觉效果(如有)
步骤 4:代码集成(gameplay-programmer)
生成 gameplay-programmer 代理以:
- 实现音频管理器系统或审查现有系统
- 将音频事件连接到游戏性触发器
- 实现自适应音乐系统(如已指定)
- 设置音频遮挡(Occlusion)和混响区域(Reverb Zones)
- 编写音频事件触发的单元测试
-
编制音频设计文档,整合所有团队的输出。
-
保存至
design/gdd/audio-[feature].md。 -
输出摘要,包含:音频事件数量、预估资产数量、实现任务清单,以及团队成员之间的待决问题。
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.
- 1mo ago First seen · 70 lines · 42 tokens per session scan A c4d717c851b8
team-audio is a skill published in the GitHub repository pixel-cellar/Claude-Code-Game-Studios (361 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 950 once invoked, about $0.0002 per session on Opus 5.5. 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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