Skills photo-video-maker-for-marketing

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 "$T/skills/bwbernardweston18/photo-video-maker-for-marketing" ~/.claude/skills/openclaw-skills-photo-video-maker-for-marketing && rm -rf "$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 "$T/skills/bwbernardweston18/photo-video-maker-for-marketing" ~/.openclaw/skills/openclaw-skills-photo-video-maker-for-marketing && rm -rf "$T"
manifest: skills/bwbernardweston18/photo-video-maker-for-marketing/SKILL.md
source content

Getting Started

Ready when you are. Drop your images and photos here or describe what you want to make.

Try saying:

  • "create five product photos in JPG format into a 1080p MP4"
  • "turn these product photos into a 30-second promotional video with text overlays and background music"
  • "creating promotional videos from product photos for social media ads for 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.

Photo Video Maker for Marketing — Turn Photos into Marketing Videos

Send me your images and photos and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload five product photos in JPG format, type "turn these product photos into a 30-second promotional video with text overlays and background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: use consistent image dimensions across all photos to avoid cropping issues in the final video.

Matching Input to Actions

User prompts referencing photo video maker for marketing, 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.

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

HeaderValue
X-Skill-Source
photo-video-maker-for-marketing
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":"<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

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

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)

Common Workflows

Quick edit: Upload → "turn these product photos into a 30-second promotional video with text overlays and background music" → 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 "turn these product photos into a 30-second promotional video with text overlays and background music" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across ad platforms like Meta and Google Ads.