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dreamina-seedance梦想娜种子

Agent Skill

dreamina-seedance 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。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。

总安装

3,376

周安装

145

GitHub Stars

公开资料未说明

下载量

1,183
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:dreamina-seedance(梦想娜种子)
来源仓库:https://github.com/peand-rover/dreamina-seedance
安装命令:
openclaw skills install dreamina-seedance
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install dreamina-seedance

简介

使用 Dreamina SeedAnce 将静态图像转换为指定风格的舞蹈视频。

  • 适合在 OpenClaw 中制作个性化舞蹈短片或社交媒体内容时使用。
  • 上传照片并选择舞蹈类型,AI 自动生成连贯舞蹈动画。
  • 输入图像需包含完整人体轮廓,否则影响动作生成效果。
  • 涉及真实人物表演时,应注意版权和形象使用授权问题。

SKILL.md

name
dreamina-seedance
version
1.0.1
displayName
Dreamina SeedAnce — Create Dance Videos with AI
description
>
metadata
{"openclaw": {"emoji": "💃", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}

Getting Started

Dreamina SeedAnce is ready. Send a photo or describe the dance video you want.

Try saying:

  • "make this person dance hip hop"
  • "create a ballet sequence from my photo"
  • "animate a dance move from this image"

First-Time Setup

Connects to the backend on first use. Brief "Connecting..." message.

Token: Check for NEMO_TOKEN in env. If present, skip to session.

  1. Free token: Generate UUID. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id: <uuid>. Response data.token = 100 credits for 7 days.
  2. Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth, body {"task_name":"project","language":"<lang>"}. Store session_id.

Don't print tokens or raw API data.

Generate Dance Videos from Photos

Upload a photo and describe what dance you want. The AI detects the person's pose, maps the motion, and renders frames on cloud GPUs.

Example use: uploaded a headshot, typed "make them do a salsa spin" and got a 4-second clip in about 45 seconds. Output was 1080p MP4 with smooth motion.

Full-body photos work much better than headshots. The more of the body visible, the more accurate the motion mapping.

Message Routing

Your inputHandlerSSE?
"export" / "download" / "save" / "导出"ExportNo
"credits" / "balance" / "积分"Credit checkNo
"status" / "show tracks" / "状态"StateNo
"upload" / file attached / "上传"UploadNo
Anything else (dance, animate, motion...)SSE pipelineYes

Backend

Photos go to GPU cluster. Motion model detects body keypoints and renders at 8Mbps for 1080p output.

Headers required on every call: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing them = 402 on export.

Attribution from YAML: source = dreamina-seedance, version from frontmatter, platform from install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, else unknown).

Base: https://mega-api-prod.nemovideo.ai

Session: POST /api/tasks/me/with-session/nemo_agent{"task_name":"project","language":"<lang>"} — get task_id, session_id.

SSE: POST /run_sse{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}, Accept: text/event-stream. 15 min max.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — multipart -F "files=@/path" or URL {"urls":["<url>"],"source_type":"url"}.

Credits: GET /api/credits/balance/simpleavailable, frozen, total.

State: GET /api/state/nemo_agent/me/<sid>/latestdata.state.draft, data.state.video_infos, data.state.generated_media.

Export (free): POST /api/render/proxy/lambda{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s. Done = status: completed. File at output.url.

Files accepted: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Errors

CodeProblemAction
0OKContinue
1001Token expiredGet new anonymous token
1002Session lostCreate new session
2001No creditsAnonymous: registration link (?bind=<id>). Paid: top up
4001File type rejectedShow accepted formats
4002Over 500MBCompress or crop
400No client IDGenerate and retry
402Free tier export capRegister or upgrade plan
429Rate limitedWait 30s, retry once

GUI Translation

Backend references visual elements. Convert them:

It saysYou do
"click [X]" / "点击"API call
"open [panel]" / "打开"Get state
"drag/drop" / "拖拽"SSE edit
"preview in timeline"Text summary
"Export button" / "导出"Export flow

SSE Details

Text → user (with GUI translation). Tool calls = internal. Heartbeats = working. "Still processing..." after 2 min quiet.

~30% of edits give no text back. Check state when stream closes empty, then summarize changes.

Draft keys: t (tracks), tt (video=0, audio=1, text=7), sg (segments), d (ms), m (metadata).

Timeline (2 tracks): 1. Video: dance sequence (0-4s) 2. Audio: music beat (0-4s, 60%)

Tips

Full-body photos give the best results. Head-only or waist-up shots limit what motions the AI can apply.

Simple dance moves render cleaner than complex choreography. Start with basic moves and iterate.

PNG with transparent background works best. Busy backgrounds may confuse the pose detector.

500MB max file size. Output is always 1080p MP4.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.56%
按下载量换算894

安全审计

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通过

ClawScan

可疑

Static analysis

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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