Upload Video

v1.0.0

edit video files into processed video files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for uploading raw foot...

0· 68·0 current·0 all-time
bypeandrover adam@peand-rover

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for peand-rover/upload-video.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Upload Video" (peand-rover/upload-video) from ClawHub.
Skill page: https://clawhub.ai/peand-rover/upload-video
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install upload-video

ClawHub CLI

Package manager switcher

npx clawhub@latest install upload-video
Security Scan
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Purpose & Capability
The name/description (upload & edit videos) matches the runtime instructions and required credential (NEMO_TOKEN). Declared API endpoints, upload and render flows, and headers are appropriate for a remote video-processing service.
Instruction Scope
SKILL.md instructs the agent to create sessions, upload user files, stream SSE events, poll job state, and download result URLs — all expected for this purpose. It also includes logic to obtain an anonymous token if NEMO_TOKEN is absent (POST to the service). No instructions ask the agent to read unrelated system files or exfiltrate data to other endpoints. Minor note: the file asks to ‘keep the technical details out of the chat,’ which is operational guidance but not itself a red flag.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. That is the lowest-risk install model.
Credentials
Only NEMO_TOKEN is required (declared as primaryEnv), which is proportional to a service that requires authorization. However there is a small inconsistency: the top-level registry metadata listed no required config paths, but the SKILL.md frontmatter metadata references a config path (~/.config/nemovideo/) — the skill does not otherwise instruct reading that path. This mismatch is likely benign but should be clarified.
Persistence & Privilege
The skill is not always-enabled, does not request elevated or persistent platform privileges, and does not alter other skills' configs. Autonomous invocation is enabled by default on the platform but is not an unusual or additional privilege here.
Assessment
This skill will send any videos you drop into the chat to a remote nemo backend (https://mega-api-prod.nemovideo.ai) for processing, so do not upload sensitive or confidential footage unless you trust that service and its privacy policy. If you provide your own NEMO_TOKEN you give the skill access to that account — only do so for trusted services. If you do not provide a token, the skill will obtain an anonymous starter token by calling the service (this creates transient credentials on the provider). Note the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) even though registry metadata did not — ask the author to clarify whether the agent will read that local path. Finally, confirm you are comfortable with network transfers, remote storage of rendered files, and any download URLs the service returns before using the skill.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

📤 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk975yzvzgsxm8m8w5jt2fb98x1850pyr
68downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

Share your video files and I'll get started on AI video processing. Or just tell me what you're thinking.

Try saying:

  • "edit my video files"
  • "export 1080p MP4"
  • "trim the silent parts and add"

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.

Upload Video — Upload, Edit and Export Videos

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

Here's a typical use: you send a a 2-minute phone recording in MOV format, ask for trim the silent parts and add subtitles in English, and about 30-60 seconds 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 3 minutes process significantly faster.

Matching Input to Actions

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

User says...ActionSkip 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.

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

HeaderValue
X-Skill-Sourceupload-video
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

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

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

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

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

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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.

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Backend Response Translation

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

Backend saysYou 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

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)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Common Workflows

Quick edit: Upload → "trim the silent parts and add subtitles in English" → Download MP4. Takes 30-60 seconds 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 "trim the silent parts and add subtitles in English" — concrete instructions get better results.

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

H.264 codec gives the best balance of quality and file size.

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