Clip Assistant

v1.0.0

Turn a 2-minute raw interview recording into 1080p edited video clips just by typing what you need. Whether it's trimming and enhancing short clips for socia...

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bypeandrover adam@peand-rover

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for peand-rover/clip-assistant.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Clip Assistant" (peand-rover/clip-assistant) from ClawHub.
Skill page: https://clawhub.ai/peand-rover/clip-assistant
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 clip-assistant

ClawHub CLI

Package manager switcher

npx clawhub@latest install clip-assistant
Security Scan
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medium confidence
Purpose & Capability
The name and description (cloud video clip editing) match the declared requirement (NEMO_TOKEN) and the SKILL.md instructions that call a nemo-video API to create sessions, upload video, and request renders. No unrelated credentials or binaries are requested.
Instruction Scope
Instructions stay within the editing/export workflow (session creation, SSE, upload, render polling). They explicitly instruct the agent to upload user video files and make POST/GET requests to the external nemo API. This means user media and related metadata will be sent to that third-party service; the skill also supports obtaining an anonymous token if NEMO_TOKEN is not present. There are no instructions to read unrelated local files or environment variables.
Install Mechanism
No install spec or code files — instruction-only skill. Nothing is written to disk or downloaded by an install step, which lowers risk.
Credentials
The only required credential is NEMO_TOKEN (declared as primary), which is proportional for a cloud API. However, SKILL.md frontmatter references a config path (~/.config/nemovideo/) while the registry metadata said no required config paths — a minor inconsistency to clarify. The skill's anonymous-token flow can create a short-lived token if the env var is absent.
Persistence & Privilege
always is false and there is no install-time persistence. The skill does not request system-wide config changes or access to other skills' configs.
Assessment
This skill sends any uploaded videos and editing commands to a nemo-video backend (mega-api-prod.nemovideo.ai) and needs a NEMO_TOKEN (or will request an anonymous token). Before installing or using it, confirm you trust that external service and its privacy/retention policy — do not upload sensitive or confidential footage. Verify where you obtained NEMO_TOKEN (only provide tokens from a trusted source). Note the small metadata mismatch: SKILL.md references ~/.config/nemovideo/ but registry metadata did not list config paths — ask the publisher to clarify. If you need source code or an official homepage for auditability, request that from the owner; absence of a published homepage reduces traceability.

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

Runtime requirements

✂️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97bsgaqrepe1h8kh1nmypy7hn850x28
64downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "edit my video clips"
  • "export 1080p MP4"
  • "trim the best 30 seconds and"

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.

Clip Assistant — Edit and Export Video Clips

Drop your video clips in the chat and tell me what you need. I'll handle the AI clip editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute raw interview recording, ask for trim the best 30 seconds and add a text overlay with my channel name, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing clip assistant, 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.

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

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

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

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.

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.

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

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the best 30 seconds and add a text overlay with my channel name" — 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 all platforms.

Common Workflows

Quick edit: Upload → "trim the best 30 seconds and add a text overlay with my channel name" → 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.

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