Trimmer Canva

v1.0.0

Get trimmed video clips ready to post, without touching a single slider. Upload your raw video clips (MP4, MOV, WebM, AVI, up to 500MB), say something like "...

0· 63·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dsewell-583h0/trimmer-canva.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Trimmer Canva" (dsewell-583h0/trimmer-canva) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/trimmer-canva
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 trimmer-canva

ClawHub CLI

Package manager switcher

npx clawhub@latest install trimmer-canva
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
Name/description (trim Canva-exported videos) aligns with the runtime instructions which call a remote video-processing API. Declared primary credential (NEMO_TOKEN) and endpoints match the expected need to authenticate to a third-party render service.
Instruction Scope
Instructions are focused on creating sessions, uploading media, streaming SSE edits, polling export status and returning a download URL — all consistent with a cloud trimming service. Important privacy note: user-supplied video/audio files are uploaded to the external domain. The SKILL.md also instructs generating anonymous tokens when NEMO_TOKEN is absent. There is no instruction to read arbitrary local files or unrelated environment variables.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is the lowest-risk install profile.
Credentials
Only a single credential (NEMO_TOKEN) is required and used as a bearer token for the service. The metadata lists a config path (~/.config/nemovideo/) but the runtime instructions do not instruct reading that path. Re-issuing anonymous tokens when missing is documented. Users should consider what privileges the NEMO_TOKEN grants on the remote service.
Persistence & Privilege
always:false and no install steps that modify other skills or system state. The skill does not request permanent presence or elevated platform privileges.
Assessment
This skill appears to do what it says: it will upload your videos to nemo's cloud rendering service and return trimmed exports. Before installing or using it: (1) Confirm you trust the external domain (mega-api-prod.nemovideo.ai) and the unknown publisher — there is no homepage or provenance provided. (2) Do not supply a high-privilege token; check what permissions the NEMO_TOKEN grants and prefer an account/token with limited scope or use the anonymous flow for testing. (3) Test with non-sensitive, short clips first to verify behavior and output. (4) Be aware that uploaded media will leave your device and may be stored/processed by the remote service; review any available privacy/terms if you can locate them. (5) If you need the skill to avoid sending certain sensitive content, do not use it until you can confirm the provider's policies. If you want higher assurance, ask the publisher for a homepage, documentation, or a public audit of their API before proceeding.

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

Runtime requirements

✂️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk975cbvxxhns13efz1mbryekmh851pbq
63downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "trim my raw video clips"
  • "export 1080p MP4"
  • "trim the intro and outro, cut"

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.

Trimmer for Canva Videos — Trim and Export Canva Videos

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

Say you have a 3-minute Canva-exported MP4 presentation and want to trim the intro and outro, cut dead air between slides — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: export your Canva video at original quality before uploading for the cleanest trim result.

Matching Input to Actions

User prompts referencing trimmer canva, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

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

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.

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)

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.

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 intro and outro, cut dead air between slides" → 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 intro and outro, cut dead air between slides" — concrete instructions get better results.

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

Export as MP4 from Canva before uploading for widest compatibility and best re-encoding quality.

Comments

Loading comments...