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Agent Skill · 开发

acestep(acestep 音频)

acestep 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

acestep 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 17,697。

总安装 388周安装 16GitHub Stars 3,110下载 127核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:acestep(acestep 音频)
来源仓库:https://github.com/calesthio/openmontage
仓库路径:skills/acestep
安装命令:
npx skills add https://github.com/calesthio/openmontage --skill acestep
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/calesthio/openmontage --skill acestep

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

acestep 提供基于 ACE-Step 1.5 的音乐生成能力,支持通过命令行工具生成指定风格与时长音频。它适用于视频背景配乐、播客配音或广告音效制作,支持 BPM、调性和场景预设控制。

使用时需在 .env 中配置 RUNPOD_API_KEY 和 ENDPOINT_ID,依赖 agent-browser 技能实现 PNG 渲染。注意输出 URL 有效期仅 10 分钟,需及时下载避免失效。acestep 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/acestep

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/calesthio/openmontage --skill acestep;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

acestep 怎么安装?

在终端执行 npx skills add https://github.com/calesthio/openmontage --skill acestep。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

acestep 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

acestep 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

acestep 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

acestep 用的人多吗?

公开数据是累计安装 388 次,近一周安装 16 次,下载 127 次,GitHub 3,110 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

acestep 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,110 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
acestep

acestep 音频 · 本页

3883,110需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

ACE-Step 1.5 Music Generation

Open-source music generation (MIT license) via tools/music_gen.py. Runs on RunPod serverless. Requires RUNPOD_API_KEY and RUNPOD_ACESTEP_ENDPOINT_ID in .env (run --setup to create endpoint).

Quick Reference

# Basic generation
python tools/music_gen.py --prompt "Upbeat tech corporate" --duration 60 --output bg.mp3

# With musical control
python tools/music_gen.py --prompt "Calm ambient piano" --duration 30 --bpm 72 --key "D Major" --output ambient.mp3

# Scene presets (video production)
python tools/music_gen.py --preset corporate-bg --duration 60 --output bg.mp3
python tools/music_gen.py --preset tension --duration 20 --output problem.mp3
python tools/music_gen.py --preset cta --brand digital-samba --duration 15 --output cta.mp3

# Vocals with lyrics
python tools/music_gen.py --prompt "Indie pop jingle" --lyrics "[verse]\nBuild it better\nShip it faster" --duration 30 --output jingle.mp3

# Cover / style transfer
python tools/music_gen.py --cover --reference theme.mp3 --prompt "Jazz piano version" --duration 60 --output jazz_cover.mp3

# Stem extraction
python tools/music_gen.py --extract vocals --input mixed.mp3 --output vocals.mp3

# List presets
python tools/music_gen.py --list-presets

Creating a Song (Step by Step)

1. Instrumental background track (simplest)

python tools/music_gen.py --prompt "Upbeat indie rock, driving drums, jangly guitar" --duration 60 --bpm 120 --key "G Major" --output track.mp3

2. Song with vocals and lyrics

Write lyrics in a temp file or pass inline. Use structure tags to control song sections.

# Write lyrics to a file first (recommended for longer songs)
cat > /tmp/lyrics.txt << 'LYRICS'
[Verse 1]
Walking through the morning light
Coffee in my hand feels right
Another day to build and dream
Nothing's ever what it seems

[Chorus - anthemic]
WE KEEP MOVING FORWARD
Through the noise and doubt
We keep moving forward
That's what it's about

[Verse 2]
Screens are glowing late at night
Shipping code until it's right
The deadline's close but so are we
Almost there, just wait and see

[Chorus - bigger]
WE KEEP MOVING FORWARD
Through the noise and doubt
We keep moving forward
That's what it's about

[Outro - fade]
(Moving forward...)
LYRICS

# Generate the song
python tools/music_gen.py \
  --prompt "Upbeat indie rock anthem, male vocal, driving drums, electric guitar, studio polish" \
  --lyrics "$(cat /tmp/lyrics.txt)" \
  --duration 60 \
  --bpm 128 \
  --key "G Major" \
  --output my_song.mp3

3. Using a preset for video background

python tools/music_gen.py --preset tension --duration 20 --output problem_scene.mp3

Key tips for good results

  • Caption = overall style (genre, instruments, mood, production quality)
  • Lyrics = temporal structure (verse/chorus flow, vocal delivery)
  • UPPERCASE in lyrics = high vocal intensity
  • Parentheses = background vocals: "We rise (together)"
  • Keep 6-10 syllables per line for natural rhythm
  • Don't describe the melody in the caption — describe the *sound* and *feeling*
  • Use --seed to lock randomness when iterating on prompt/lyrics

Scene Presets

PresetBPMKeyUse Case
corporate-bg110C MajorProfessional background, presentations
upbeat-tech128G MajorProduct launches, tech demos
ambient72D MajorOverview slides, reflective content
dramatic90D MinorReveals, announcements
tension85A MinorProblem statements, challenges
hopeful120C MajorSolution reveals, resolutions
cta135E MajorCall to action, closing energy
lofi85F MajorScreen recordings, coding demos

Task Types

text2music (default)

Generate music from text prompt + optional lyrics.

cover

Style transfer from reference audio. Control blend with --cover-strength (0.0-1.0):

  • 0.2 — Loose style inspiration (more creative freedom)
  • 0.5 — Balanced style transfer
  • 0.7 — Close to original structure (default)
  • 1.0 — Maximum fidelity to source

extract

Stem separation — isolate individual tracks from mixed audio. Tracks: vocals, drums, bass, guitar, piano, keyboard, strings, brass, woodwinds, other

repaint (future)

Regenerate a specific time segment within existing audio while preserving the rest.

lego (future, requires base model)

Generate individual instrument tracks within an existing audio context.

complete (future, requires base model)

Extend partial compositions by adding specified instruments.

Prompt Engineering

Caption Writing — Layer Dimensions

Write captions by layering multiple descriptive dimensions rather than single-word descriptions.

Dimensions to include:

  • Genre/Style: pop, rock, jazz, electronic, lo-fi, synthwave, orchestral
  • Emotion/Mood: melancholic, euphoric, dreamy, nostalgic, intimate, tense
  • Instruments: acoustic guitar, synth pads, 808 drums, strings, brass, piano
  • Timbre: warm, crisp, airy, punchy, lush, polished, raw
  • Era: "80s synth-pop", "modern indie", "classical romantic"
  • Production: lo-fi, studio-polished, live recording, cinematic
  • Vocal: breathy, powerful, falsetto, raspy, spoken word (or "instrumental")

Good: "Slow melancholic piano ballad with intimate female vocal, warm strings building to powerful chorus, studio-polished production" Bad: "Sad song"

Key Principles

  1. Specificity over vagueness — describe instruments, mood, production style
  2. Avoid contradictions — don't request "classical strings" and "hardcore metal" simultaneously
  3. Repetition reinforces priority — repeat important elements for emphasis
  4. Sparse captions = more creative freedom — detailed captions constrain the model
  5. Use metadata params for BPM/key — don't write "120 BPM" in the caption, use --bpm 120

Lyrics Formatting

Structure tags (use in lyrics, not caption):

[Intro]
[Verse]
[Chorus]
[Bridge]
[Outro]
[Instrumental]
[Guitar Solo]
[Build]
[Drop]
[Breakdown]

Vocal control (prefix lines or sections):

[raspy vocal]
[whispered]
[falsetto]
[powerful belting]
[harmonies]
[ad-lib]

Energy indicators:

  • UPPERCASE = high intensity ("WE RISE ABOVE")
  • Parentheses = background vocals ("We rise (together)")
  • Keep 6-10 syllables per line within sections for natural rhythm

Example — Tech Product Jingle:

[Verse]
Build it better, ship it faster
Every feature tells a story

[Chorus - anthemic]
THIS IS YOUR PLATFORM
Your vision, your stage
Digital Samba, every page

[Outro - fade]
(Build it better...)

Video Production Integration

Music for Scene Types

ScenePresetDurationNotes
Titledramatic or ambient3-5sShort, mood-setting
Problemtension10-15sDark, unsettling
Solutionhopeful10-15sRelief, optimism
Demolofi or corporate-bg30-120sNon-distracting, matches demo length
Statsupbeat-tech8-12sBuilding credibility
CTActa5-10sMaximum energy, punchy
Creditsambient5-10sGentle fade-out

Timing Workflow

  1. Plan scene durations first (from voiceover script)
  2. Generate music to match: --duration <scene_seconds>
  3. Music duration is precise (within 0.1s of requested)
  4. For background music spanning multiple scenes: generate one long track

Combining with Voiceover

Background music should be mixed at 10-20% volume in Remotion:

<Audio src={staticFile('voiceover.mp3')} volume={1} />
<Audio src={staticFile('bg-music.mp3')} volume={0.15} />

For music under narration: use instrumental presets (corporate-bg, ambient, lofi). For music-forward scenes (title, CTA): can use higher volume or vocal tracks.

Brand Consistency

Use --brand <name> to load hints from brands/<name>/brand.json. Use --cover --reference brand_theme.mp3 to create variations of a brand's sonic identity. For consistent sound across a project: fix the seed (--seed 42) and vary only duration/prompt.

Technical Details

  • Output: 48kHz MP3/WAV/FLAC
  • Duration range: 10-600 seconds
  • BPM range: 30-300
  • Inference: ~2-3s on GPU (turbo, 8 steps), ~40-60s on Mac MPS
  • Turbo model: 8 steps, no CFG needed, fast and good quality
  • Shift parameter: 3.0 recommended for turbo (improves quality)

When NOT to use ACE-Step

  • Voice cloning — use Qwen3-TTS or ElevenLabs instead
  • Sound effects — use ElevenLabs SFX (tools/sfx.py)
  • Speech/narration — use voiceover tools, not music gen
  • Stem extraction from video — extract audio first with FFmpeg, then use --extract

平台分布

Codex

35.56%
按下载量换算45

Claude

29.51%
按下载量换算37

Cursor

19.71%
按下载量换算25

Gemini CLI

9.84%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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