Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Lord1Egypt/awesome-skill-forgenpx agentmods add skills/lord1egypt/awesome-skill-forge/ace-step-musicWrote 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/lord1egypt/awesome-skill-forge/ace-step-music)<a href="https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/ace-step-music"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/ace-step-music/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/lord1egypt/awesome-skill-forge/ace-step-music"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/ace-step-music.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 | $0.00000 | $0.01603 |
| Opus 5 | $0.00000 | $0.00801 |
| Sonnet 5 | $0.00000 | $0.00321 |
| Haiku 4.5 | $0.00000 | $0.00160 |
Grade A, and why
ace-step-music 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ACE-Step 1.5 Skill for OpenClaw
概述
本 Skill 提供在 Apple Silicon Mac (M1/M2/M3/M4) 上自动化部署和调用 ACE-Step 1.5 音乐生成模型的能力。
环境要求
最低配置
- 芯片: Apple Silicon (M1/M2/M3/M4)
- 内存: 16GB (32GB 推荐)
- 存储: 10GB 可用空间
- 系统: macOS 13.0+
推荐配置 (主人设备)
- 芯片: M2
- 内存: 32GB ✅ 超额满足
- 存储: 485GB 可用 ✅
- 后端: MLX (Apple Silicon 原生优化)
安装步骤
1. 环境准备
# 检查 Python 版本 (需要 3.10+)
python3 --version
# 创建虚拟环境 (推荐)
python3 -m venv ~/ace-step-env
source ~/ace-step-env/bin/activate
# 升级 pip
pip install --upgrade pip
2. 安装 ACE-Step
# 克隆仓库
git clone https://github.com/ace-step/ACE-Step-1.5.git ~/workspace/ace-step
cd ~/workspace/ace-step
# macOS 使用 MLX 后端安装
pip install -e ".[mlx]"
# 或使用官方脚本
./scripts/install_macos.sh
3. 下载模型权重
# 自动下载 (首次运行时会自动下载)
# 或手动从 HuggingFace 下载
huggingface-cli download ace-step/ACE-Step-1.5 --local-dir ./models
4. 验证安装
# 运行测试生成
python -m ace_step.generate --prompt "A peaceful piano melody" --output test.wav
使用方法
基础生成
from ace_step import MusicGenerator
# 初始化生成器 (MLX 后端自动识别)
generator = MusicGenerator(
model_path="./models",
device="mps", # Metal Performance Shaders
precision="float16"
)
# 生成音乐
music = generator.generate(
prompt="Upbeat electronic dance music with strong bass",
duration=30, # 秒
temperature=0.8
)
# 保存
music.save("output.wav")
高级配置
config = {
"backend": "mlx", # Apple Silicon 最优
"device": "mps", # Metal Performance Shaders
"precision": "float16", # 平衡速度和质量
"max_memory": "24GB", # 保留 8GB 给系统
"quantize": "int8", # 可选:进一步加速
"sampling_rate": 44100,
"channels": 2
}
generator = MusicGenerator(**config)
Agent 调用接口
工具函数
async def generate_music(
prompt: str,
duration: int = 30,
style: str = "auto",
output_path: str = "./output.wav"
) -> dict:
"""
生成音乐文件
Args:
prompt: 音乐描述文本
duration: 时长(秒),默认30
style: 风格提示,可选
output_path: 输出路径
Returns:
{
"success": bool,
"file_path": str,
"duration": float,
"generation_time": float
}
"""
pass
async def check_installation() -> dict:
"""检查 ACE-Step 安装状态"""
pass
async def get_system_info() -> dict:
"""获取当前系统性能和配置信息"""
pass
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.
- 12d ago First seen · 259 lines · 0 tokens per session scan A ab6fabc845d5
ace-step-music is a skill published in the GitHub repository Lord1Egypt/awesome-skill-forge (2 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,603 tokens. 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 2026-08-31.
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