davinci-auto-editor
Generate DaVinci Resolve import packages from local media plus a cloud editing API. Use when Codex needs to scan a material folder, request a cloud editing plan, and write a Resolve-importable EDL package with pure Node on the user machine.
Best use case
davinci-auto-editor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Generate DaVinci Resolve import packages from local media plus a cloud editing API. Use when Codex needs to scan a material folder, request a cloud editing plan, and write a Resolve-importable EDL package with pure Node on the user machine.
Teams using davinci-auto-editor should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/davinci-auto-editor/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How davinci-auto-editor Compares
| Feature / Agent | davinci-auto-editor | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate DaVinci Resolve import packages from local media plus a cloud editing API. Use when Codex needs to scan a material folder, request a cloud editing plan, and write a Resolve-importable EDL package with pure Node on the user machine.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# DaVinci Auto Editor 使用这个 skill 时，按下面顺序执行： 1. 读取 `examples/config.example.json` 同结构的配置文件。 2. 校验 `api_base_url`、`api_key`、`material_path`、`timeline_fps` 等关键参数。 3. 递归扫描素材目录，并向云端上报素材索引。 4. 调用云端 API 创建任务并获取剪辑计划。 5. 在本地只生成最小执行计划，不要把完整云端内部逻辑写入本地文件。 6. 由 Node 生成 Resolve 可导入的 `timeline.edl` 和导入说明文件。 7. 将准备结果回传云端。 ## 输入参数 至少提供这些字段： - `api_base_url` - `api_key` - `project_type` - `aspect_ratio` - `material_path` - `template_id` - `subtitle_mode` - `music_policy` - `pace_policy` - `output_mode` - `render_preset` - `timeline_fps` - `timeline_resolution` 可选字段： - `task_timeout_ms` - `poll_interval_ms` - `request_timeout_ms` - `task_name` - `webhook_url` - `extra_metadata` ## 输出结果 默认在素材目录旁创建 `_davinci_auto_editor/<taskId>/`，包含： - `resolve-import.json`：最小本地导入计划 - `timeline.edl`：Resolve 导入文件 - `IMPORT-TO-RESOLVE.txt`：导入说明 - `execution-report.json`：本地执行报告 ## 推荐工作流 - 把核心决策、模板逻辑、API Key 鉴权和配额管理放在云端服务。 - 本地只保留素材扫描、结果导出和回传逻辑。 - 优先使用短路径、稳定命名的素材目录，减少 EDL relink 成本。 - 在正式任务前先用样本素材验证时间线 FPS 和素材命名。 ## 依赖要求 - Node.js 18 或更高版本 - 已安装 DaVinci Resolve - 可访问云端 API 的网络环境 ## 错误处理原则 - 缺少配置、素材目录不存在、API 调用失败时立即停止并返回非 0 退出码。 - 始终写出 `execution-report.json` 以便排查。 - 不在本地输出完整云端推理结果，只输出导入所需的最小执行数据。 - 明确提示第一版只覆盖基础拼接和时间线导入准备。
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