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Ai Video Enhancer

作者 vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-video-enhancer
功能描述
Skip the learning curve of professional editing software. Describe what you want — upscale this video to 1080p and reduce the noise — and get upscaled MP4 vi...
使用说明 (SKILL.md)

Getting Started

Share your low-quality video and I'll get started on AI video enhancement. Or just tell me what you're thinking.

Try saying:

  • "enhance my low-quality video"
  • "export 1080p MP4"
  • "upscale this video to 1080p and"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

AI Video Enhancer — Upscale and Sharpen Your Videos

Drop your low-quality video in the chat and tell me what you need. I'll handle the AI video enhancement on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 60-second 480p phone recording, ask for upscale this video to 1080p and reduce the noise, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 2 minutes process significantly faster.

Matching Input to Actions

User prompts referencing ai video enhancer, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source ai-video-enhancer
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

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

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Common Workflows

Quick edit: Upload → "upscale this video to 1080p and reduce the noise" → Download MP4. Takes 1-2 minutes for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "upscale this video to 1080p and reduce the noise" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 with H.264 codec for the best balance of quality and file size.

安全使用建议
This skill appears to be what it says: it sends uploaded videos to a third‑party API (mega-api-prod.nemovideo.ai) for cloud processing and requires a NEMO_TOKEN (or will obtain an anonymous one for you). Before installing or using it: 1) Do not upload sensitive or private videos unless you trust the service and its privacy policy; the publisher has no homepage and is anonymous, so verify the service if possible. 2) Prefer supplying your own NEMO_TOKEN from a trusted account rather than relying on the anonymous token fallback. 3) Note the small metadata mismatch (a config path listed in the SKILL.md frontmatter) — this is likely a packaging oversight but worth confirming with the publisher if you require stricter provenance. 4) If you need stronger assurance, ask the publisher for a canonical homepage, privacy policy, or open source code before sending real production data.
功能分析
Type: OpenClaw Skill Name: ai-video-enhancer Version: 1.0.0 The skill is a standard integration for a cloud-based video enhancement service (nemovideo.ai). It provides instructions for the agent to manage authentication, upload video files, and poll for rendering status via a series of REST API calls. While it requires network access and handles an API token (NEMO_TOKEN), all behaviors are strictly aligned with the stated purpose of upscaling and sharpening videos, with no evidence of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
The name/description map to the actions in SKILL.md (session creation, upload, render/export). Requesting a single NEMO_TOKEN credential is expected for a third‑party video API. However, the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) in metadata while the registry metadata provided earlier reported no required config paths — this mismatch is an inconsistency that may be a packaging oversight. The API base (mega-api-prod.nemovideo.ai) and the skill owner are unknown (no homepage), which reduces confidence in provenance but does not by itself make the behavior incoherent.
Instruction Scope
The instructions are explicit about network calls: obtaining an anonymous token if NEMO_TOKEN is absent, creating a session, uploading videos, and polling a render endpoint. All of that is within the stated purpose. Important privacy/consent implications: the skill instructs uploading user video files (or URLs) to an external cloud service — that is necessary for cloud-based enhancement but should be called out to users because it transmits potentially sensitive media. The instructions do not tell the agent to read unrelated local files or arbitrary secrets beyond NEMO_TOKEN.
Install Mechanism
Instruction-only skill with no install spec or code files. This minimizes disk persistence and supply-chain risk. There are no downloads or package installs declared.
Credentials
Only one environment variable (NEMO_TOKEN) is required, which is proportionate for calling the named API. The skill will fall back to creating an anonymous token via the API if NEMO_TOKEN is absent; that fallback requires making a network POST with a generated UUID. There are no unrelated credentials requested. Users should be aware that an anonymous token grants the same processing rights (and transient credits) and will be created/used if they don't provide their own token.
Persistence & Privilege
always:false and no install or system modifications. The skill does require session tokens for API use but does not request persistent system privileges or attempt to change other skills' configs. Autonomous invocation is allowed by platform default but is not combined with other high‑risk factors here.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ai-video-enhancer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-enhancer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of AI Video Enhancer for easy cloud-based video upscaling and sharpening. - Supports MP4, MOV, AVI, and WebM uploads up to 500MB; no local software needed. - Simple, chat-based interface: just describe video enhancement needs and receive upscaled MP4s in minutes. - Handles authentication and session management automatically, including free anonymous starter credits. - Cloud GPU processing with real-time status updates and clear error handling. - Designed for creators and social media users looking to improve video quality fast.
元数据
Slug ai-video-enhancer
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Ai Video Enhancer 是什么?

Skip the learning curve of professional editing software. Describe what you want — upscale this video to 1080p and reduce the noise — and get upscaled MP4 vi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 95 次。

如何安装 Ai Video Enhancer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-video-enhancer」即可一键安装,无需额外配置。

Ai Video Enhancer 是免费的吗?

是的,Ai Video Enhancer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ai Video Enhancer 支持哪些平台?

Ai Video Enhancer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ai Video Enhancer?

由 vynbosserman65(@vynbosserman65)开发并维护,当前版本 v1.0.0。

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