Skills unlimited-video-editing-with

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/unlimited-video-editing-with" ~/.claude/skills/openclaw-skills-unlimited-video-editing-with && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bwbernardweston18/unlimited-video-editing-with" ~/.openclaw/skills/openclaw-skills-unlimited-video-editing-with && rm -rf "$T"
manifest: skills/bwbernardweston18/unlimited-video-editing-with/SKILL.md
source content

Getting Started

Ready when you are. Drop your raw video clips here or describe what you want to make.

Try saying:

  • "edit a 3-minute unedited screen recording into a 1080p MP4"
  • "cut the pauses, add background music, and export as a clean 90-second clip"
  • "editing multiple videos quickly without manual timeline work for content creators and marketers"

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.

Unlimited Video Editing With AI — Edit and Export Videos Fast

This tool takes your raw video clips and runs AI video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute unedited screen recording and want to cut the pauses, add background music, and export as a clean 90-second clip — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 2 minutes process significantly faster and use fewer resources.

Matching Input to Actions

User prompts referencing unlimited video editing with, 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.

Every API call needs

Authorization: Bearer <NEMO_TOKEN>
plus the three attribution headers above. If any header is missing, exports return 402.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source
    :
    unlimited-video-editing-with
  • X-Skill-Version
    : from frontmatter
    version
  • X-Skill-Platform
    : detect from install path (
    ~/.clawhub/
    clawhub
    ,
    ~/.cursor/skills/
    cursor
    , else
    unknown
    )

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.

Error Codes

  • 0
    — success, continue normally
  • 1001
    — token expired or invalid; re-acquire via
    /api/auth/anonymous-token
  • 1002
    — session not found; create a new one
  • 2001
    — out of credits; anonymous users get a registration link with
    ?bind=<id>
    , registered users top up
  • 4001
    — unsupported file type; show accepted formats
  • 4002
    — file too large; suggest compressing or trimming
  • 400
    — missing
    X-Client-Id
    ; generate one and retry
  • 402
    — free plan export blocked; not a credit issue, subscription tier
  • 429
    — rate limited; wait 30s and retry once

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

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.

Draft field mapping:

t
=tracks,
tt
=track type (0=video, 1=audio, 7=text),
sg
=segments,
d
=duration(ms),
m
=metadata.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add background music, and export as a clean 90-second clip" — 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 widest platform compatibility.

Common Workflows

Quick edit: Upload → "cut the pauses, add background music, and export as a clean 90-second clip" → 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.