Editor Kiss

v1.0.0

Turn a 3-minute interview recording with pauses and filler words into 1080p kiss-cut edited clips just by typing what you need. Whether it's removing pauses...

⭐ 0· 34·0 current·0 all-time

by@vynbosserman65

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for vynbosserman65/editor-kiss.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "Editor Kiss" (vynbosserman65/editor-kiss) from ClawHub.
Skill page: https://clawhub.ai/vynbosserman65/editor-kiss
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-kiss

ClawHub CLI

Package manager switcher

npx clawhub@latest install editor-kiss

Security Scan

VirusTotal

Benign

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OpenClaw

Benign

medium confidence

✓

Purpose & Capability

The name/description (cloud AI kiss-cut video editing) lines up with the only required credential (NEMO_TOKEN) and the documented API endpoints. Requesting an access token for a remote editing backend is expected for this purpose.

ℹ

Instruction Scope

The SKILL.md instructs the agent to upload user media to the nemovideo backend, stream SSE responses, poll job state, and include attribution headers. All of these actions are within the stated editing purpose. It also tells the agent to detect the install path to set an X-Skill-Platform header (this requires reading the agent's install path), which is reasonable for telemetry but worth noting to privacy-conscious users.

✓

Install Mechanism

This is an instruction-only skill with no install spec or code to write to disk, so there is no package-download or install risk.

ℹ

Credentials

Only NEMO_TOKEN is required, which is proportionate for a remote editing service. The SKILL.md will auto-generate an anonymous token if none is present (via an anonymous-token endpoint). One minor inconsistency: the top-level registry summary listed no required config paths, but the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/). This mismatch should be clarified. Also remember the token grants the skill access to upload and render your media on a third-party service.

✓

Persistence & Privilege

always is false and the skill does not request elevated or platform-wide privileges. It asks to store a session_id for reuse, which is normal session state for a cloud service.

Assessment

This skill appears to do what it claims: it uploads your videos to the nemovideo backend and returns edited exports, using NEMO_TOKEN for authorization. Before installing: (1) confirm you trust the domain (mega-api-prod.nemovideo.ai) and understand that your raw media will be uploaded to that service; (2) decide whether you want to supply your own NEMO_TOKEN (tied to your account) or allow the skill to auto-generate an anonymous token (ephemeral, limited credits); (3) ask the author to resolve the small metadata mismatch (SKILL.md lists a config path that the registry summary omitted) so you know exactly what filesystem/config access the skill expects. If you have sensitive footage you don't want sent to an external cloud, do not use this skill.

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

Runtime requirements

✂️ Clawdis

EnvNEMO_TOKEN

Primary envNEMO_TOKEN

latestvk97ezdqf1zh8wcw79xkkbfdqj185pkwz

34downloads

0stars

1versions

Updated 3h ago

v1.0.0

MIT-0

Getting Started

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

Try saying:

"trim my raw video footage"
"export 1080p MP4"
"remove all dead air and jump"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Editor Kiss — Trim Dead Air Between Cuts

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

Say you have a 3-minute interview recording with pauses and filler words and want to remove all dead air and jump cuts between sentences to create smooth kiss cuts — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 5 minutes produce the most precise kiss cut detection.

Matching Input to Actions

User prompts referencing editor kiss, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
`/api/tasks/me/with-session/nemo_agent`	POST	Start a new editing session. Body: `{"task_name":"project","language":"<lang>"}`. Returns `session_id`.
`/run_sse`	POST	Send a user message. Body includes `app_name`, `session_id`, `new_message`. Stream response with `Accept: text/event-stream`. Timeout: 15 min.
`/api/upload-video/nemo_agent/me/<sid>`	POST	Upload a file (multipart) or URL.
`/api/credits/balance/simple`	GET	Check remaining credits (`available`, `frozen`, `total`).
`/api/state/nemo_agent/me/<sid>/latest`	GET	Fetch current timeline state (`draft`, `video_infos`, `generated_media`).
`/api/render/proxy/lambda`	POST	Start export. Body: `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll status every 30s.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is editor-kiss, 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).

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

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

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.

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)

Common Workflows

Quick edit: Upload → "remove all dead air and jump cuts between sentences to create smooth kiss cuts" → 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 "remove all dead air and jump cuts between sentences to create smooth kiss cuts" — 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.

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