Editor Kaise Kare

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — trim the video, add transitions, and export a clean final cut — and get po...

0· 71·0 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/editor-kaise-kare.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Editor Kaise Kare" (dsewell-583h0/editor-kaise-kare) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/editor-kaise-kare
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 editor-kaise-kare

ClawHub CLI

Package manager switcher

npx clawhub@latest install editor-kaise-kare
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
Name/description (AI cloud video editing) align with the declared primary credential (NEMO_TOKEN) and the API endpoints in SKILL.md. Small inconsistency: registry metadata lists no config paths but the SKILL.md frontmatter's openclaw.requires includes a configPath (~/.config/nemovideo/). This is not fatal but should be clarified.
Instruction Scope
SKILL.md explicitly instructs the agent to upload user video files and to call the remote nemovideo API (session creation, SSE, uploads, render polling). These operations are expected for the stated purpose, but they involve sending user content to a third-party endpoint (mega-api-prod.nemovideo.ai) and handling tokens. The instructions also require adding attribution headers and 'auto-detect' a platform from an install path (which may require reading environment/install path)—this is additional scope the user should be aware of.
Install Mechanism
Instruction-only skill with no install spec or code files. No binaries or archive downloads are requested, so there is minimal install-time risk.
Credentials
Only one credential (NEMO_TOKEN) is required, which is proportionate to a cloud API integration. The SKILL.md also documents generating an anonymous token if NEMO_TOKEN is absent. Watch for the configPath mentioned in frontmatter which could allow the skill to access ~/.config/nemovideo/ if implemented.
Persistence & Privilege
always is false and the skill does not request elevated or persistent system presence. Agent autonomous invocation is allowed (platform default) but not combined here with other broad privileges.
Assessment
This skill will upload any video files you drop into the chat to a third-party service (mega-api-prod.nemovideo.ai) and uses a NEMO_TOKEN (or an anonymously generated token) to do so. Before installing: (1) Confirm you trust the external service and are comfortable sending your videos and any metadata to it; (2) Verify the provenance of this skill (no homepage/source listed); (3) Ask the publisher to clarify the configPath discrepancy (SKILL.md frontmatter references ~/.config/nemovideo/ while registry metadata did not); (4) Avoid sending sensitive content unless you have reviewed the service's privacy terms and token handling. If you need higher assurance, request a published source/homepage or an installable package audited by a trusted party.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk972xfn278cmaa892087jx5mf985c88y
71downloads
0stars
1versions
Updated 5d ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "edit my raw video clips"
  • "export 1080p MP4"
  • "trim the video, add transitions, and"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Editor Kaise Kare — Edit and Export Finished Videos

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

Here's a typical use: you send a a 2-minute unedited phone recording, ask for trim the video, add transitions, and export a clean final cut, and about 1-2 minutes 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 editor kaise kare, 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-Sourceeditor-kaise-kare
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the video, add transitions, and export a clean final cut" — 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 platforms.

Common Workflows

Quick edit: Upload → "trim the video, add transitions, and export a clean final cut" → 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.

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