Skills en-espanol-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 "$T/skills/bwbernardweston18/en-espanol-video-editing-with" ~/.claude/skills/clawdbot-skills-en-espanol-video-editing-with && rm -rf "$T"
manifest: skills/bwbernardweston18/en-espanol-video-editing-with/SKILL.md
source content

Getting Started

Got video clips to work with? Send it over and tell me what you need — I'll take care of the Spanish language editing.

Try saying:

  • "edit a 2-minute tutorial video in English into a 1080p MP4"
  • "add Spanish subtitles and translate the voiceover to Spanish"
  • "adding Spanish subtitles and translations to existing videos for Spanish-speaking content creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if

NEMO_TOKEN
is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to
    https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token
    with header
    X-Client-Id
    set to that UUID. The response
    data.token
    is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to
    https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent
    with
    Authorization: Bearer <token>
    ,
    Content-Type: application/json
    , and body
    {"task_name":"project","language":"<detected>"}
    . Store the returned
    session_id
    for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

En Español Video Editing — Edit and Caption Videos in Spanish

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

Say you have a 2-minute tutorial video in English and want to add Spanish subtitles and translate the voiceover to Spanish — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: uploading clean audio improves Spanish transcription accuracy significantly.

Matching Input to Actions

User prompts referencing en espanol 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.

All requests must include:

Authorization: Bearer <NEMO_TOKEN>
,
X-Skill-Source
,
X-Skill-Version
,
X-Skill-Platform
. Missing attribution headers will cause export to fail with 402.

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

  • X-Skill-Source
    :
    en-espanol-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 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 → "add Spanish subtitles and translate the voiceover to Spanish" → 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 "add Spanish subtitles and translate the voiceover to Spanish" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across Spanish-language platforms.