菜单
Generate ambient background music using Lyria via the Interactions API.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | music-generation |
| description | Generate ambient background music using Lyria via the Interactions API. |
Generate background music for the radio show using the Lyria model via the Interactions API.
python3 skills/music-generation/scripts/generate_music.py --workspace ./workspace --mood tech
| Argument | Default | Description |
|---|---|---|
--workspace | workspace | Root workspace directory |
--mood | default | Music mood (see moods below) |
| Mood | Style | Pair with --style |
|---|---|---|
tech (default) | Clean synths, electronic pulse, Silicon Valley startup vibe | explainer, debate |
chill | Soft pads, gentle piano, lo-fi warmth | roundtable, explainer |
debate | Building tension, brass-like synths, panel discussion opener | debate, interview |
--mood.lyria-3-clip-preview model.{workspace}/audio/music/background.mp3.google-genai (>= 2.0.0){workspace}/audio/music/background.mp3Lyria is experimental. If generation fails with a policy error or returns no music, the script will attempt to retry once with a simpler fallback prompt: "Create a 30-second simple ambient background track. Instrumental only, calm and neutral."
If the fallback attempt also fails, the pipeline proceeds without background music — the audio-mixing step handles this gracefully.
Guides the agent on how to handle git operations and generate .patch files instead of submitting PRs.
Guides the agent on how to read and search GitHub issues to understand the repository's problems.
Records and appends every user-agent customer support interaction to the memory.md log in the workspace.
Scans a website deeply, converting HTML pages to markdown, respecting robots.txt, and updating the snapshots log.
Exposes a 100% local, offline PDF batch extraction utility (extract_to_markdown.py) that isolates invoices under invoices/ and translates PDFs into clean Markdown files for LLM-native parsing.
Reconcile loaded expenses against the pre-parsed invoice database, flagging discrepancies like amount mismatches, missing invoices, and merchant mismatches locally.