Skills time-lapse-video

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 "$T/skills/bwbernardweston18/time-lapse-video" ~/.claude/skills/clawdbot-skills-time-lapse-video && rm -rf "$T"

manifest: skills/bwbernardweston18/time-lapse-video/SKILL.md

source content

Getting Started

Share your sequential images and I'll get started on time lapse creation. Or just tell me what you're thinking.

Try saying:

"convert my sequential images"
"export 1080p MP4"
"combine these photos into a 30-second"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for

NEMO_TOKEN

in the environment. If found, skip to session creation. Otherwise:

Generate a UUID as client identifier

POST

https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token

with

X-Client-Id

header

Extract
```
data.token
```
from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST

https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent

with Bearer auth and body

{"task_name":"project"}

. Keep the returned

session_id

for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Time Lapse Video — Convert Photo Sequences Into Video

Send me your sequential images and describe the result you want. The time lapse creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload 200 photos taken every 30 seconds of a sunset, type "combine these photos into a 30-second time lapse video at 24fps", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: consistent intervals between shots produce the smoothest playback result.

Matching Input to Actions

User prompts referencing time lapse video, 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.

Include

Authorization: Bearer <NEMO_TOKEN>

and all attribution headers on every request — omitting them triggers a 402 on export.

Headers are derived from this file's YAML frontmatter.

X-Skill-Source

time-lapse-video

X-Skill-Version

comes from the

version

field, and

X-Skill-Platform

is detected from the install path (

~/.clawhub/

clawhub

~/.cursor/skills/

cursor

, otherwise

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 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=<id>` (get `<id>` 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

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

"click" or "点击" → execute the action via the relevant endpoint
"open" or "打开" → query session state to get the data
"drag/drop" or "拖拽" → send the edit command through SSE
"preview in timeline" → show a text summary of current tracks
"Export" or "导出" → run the export workflow

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty

data:

lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll

/api/state

to confirm the timeline changed, then tell the user what was updated.

Draft JSON uses short keys:

for tracks,

tt

for track type (0=video, 1=audio, 7=text),

sg

for segments,

for duration in ms,

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "combine these photos into a 30-second time lapse video at 24fps" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest platform compatibility.

Common Workflows

Quick edit: Upload → "combine these photos into a 30-second time lapse video at 24fps" → 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.