Video Editing Ai Tools List

Turn a 2-minute raw screen recording into 1080p edited video files just by typing what you need. Whether it's discovering and using AI tools to edit videos f...

Security Scan

The skill's network calls and required NEMO_TOKEN are consistent with a remote video-editing service, but there are small mismatches and scope-creep instructions (filesystem probing for attribution, automatic anonymous-token lifecycle, unclear storage of session/token data) that are not fully justified by the description.

Purpose & Capability

The skill advertises remote AI video editing and instructs the agent to call a nemovideo API for uploads, SSE editing requests, and exports — the required NEMO_TOKEN and the listed endpoints are coherent with that purpose.

Instruction Scope

Runtime instructions include automatic anonymous-token acquisition, creating and persisting session IDs, uploading user video files to the remote backend, streaming SSE handling, and mapping GUI actions to API calls — these are expected for a cloud video editor but the SKILL.md also instructs reading the skill's frontmatter and detecting install path to set attribution headers (filesystem access) and tells the agent to 'store' tokens/session_id without specifying where or how. The instructions do not document retention/cleanup of uploaded media or tokens, nor do they explicitly ask user consent before uploads.

Install Mechanism

This is an instruction-only skill with no install spec and no code files — low installation risk. No external downloads or packages are requested.

Credentials

The skill only declares a single credential, NEMO_TOKEN, which matches the described external service. However, the SKILL.md frontmatter also references a config path (~/.config/nemovideo/) and asks the agent to detect install paths for attribution — the registry metadata shown earlier did not list those config paths. That mismatch and the implied filesystem reads are disproportionate unless clearly justified.

Persistence & Privilege

always is false and the skill does not request elevated or permanent presence. It asks to persist session_id and tokens for the session, which is expected for interactive API use, but does not request changing other skills or system-wide settings.

Scan Findings in Context

[no_code_files_regex_scan] expected: The static scanner found no code because this is an instruction-only skill (SKILL.md). No code findings is expected, but absence of findings is not evidence of safety.

What to consider before installing

This skill appears to do what it claims (remote AI video editing) and only needs a single service token (NEMO_TOKEN), but you should consider privacy and token-handling details before installing: the skill will upload your videos to mega-api-prod.nemovideo.ai and may automatically fetch an anonymous token if you haven't provided one — ask the maintainer how long uploads and generated tokens are retained, where session_id/token values are stored (in-memory vs disk), and whether uploads can be disabled or require explicit consent. Also ask them to clarify the inconsistency about config paths (~/.config/nemovideo/) and the instruction to detect install paths for attribution (this requires reading filesystem locations). If you need stronger guarantees, prefer a skill that requires you to paste an explicit API key and that documents data retention and cleanup policies.

Getting Started

Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI video editing.

Try saying:

• "edit a 2-minute raw screen recording into a 1080p MP4"
• "trim silences, add captions, and apply smooth transitions"
• "discovering and using AI tools to edit videos faster for content creators"

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.

1. 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.
2. 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.

Video Editing AI Tools List — Edit and Export AI Videos

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

A quick example: upload a 2-minute raw screen recording, type "trim silences, add captions, and apply smooth transitions", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing video editing ai tools list, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: video-editing-ai-tools-list
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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

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

SSE Event Handling

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process 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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim silences, add captions, and apply smooth transitions" — 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.

Common Workflows

Quick edit: Upload → "trim silences, add captions, and apply smooth transitions" → 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.