Eb Video

edit raw video footage into edited video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and marketers use it for e...

Security Scan

The skill's requirements and runtime instructions are broadly consistent with a cloud-based video editing integration — it asks for a single service token (NEMO_TOKEN) and all actions map to the described API — but there's a small metadata inconsistency you should note before installing.

Purpose & Capability

Name/description describe cloud AI video editing and the skill only requests a single service credential (NEMO_TOKEN) and calls a nemovideo.ai API surface; that is coherent with the stated purpose. Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported 'Required config paths: none'.

Instruction Scope

The SKILL.md directs the agent to (a) use NEMO_TOKEN if present or obtain an anonymous token via the service's /api/auth/anonymous-token endpoint, (b) create a session, (c) upload user-provided media, and (d) poll for render results. It does not instruct the agent to read unrelated system files or other credentials. It does require the agent to upload user files to the remote API (expected for this purpose).

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest risk for arbitrary code being written to disk. No downloads or package installs are present.

Credentials

Only NEMO_TOKEN is required (declared primaryEnv), which is proportional to a cloud video-editing integration. Note the frontmatter's optional configPaths entry (~/.config/nemovideo/) could imply reading or storing tokens on disk; the registry metadata did not list that path. Confirm whether the skill will access or write that config path and whether tokens are persisted locally.

Persistence & Privilege

always:false and default model invocation are set — the skill does not request permanent/always-on inclusion and does not claim elevated system privileges. It does direct network calls to its API (expected).

Assessment

This skill appears to do what it says: upload videos to nemovideo.ai and return edited clips, using a single service token (NEMO_TOKEN). Before installing: (1) Verify the source/trustworthiness of the nemovideo.ai endpoint and check their privacy/storage policy because your uploaded videos will be sent to that service. (2) Confirm where tokens or session data are stored — the frontmatter mentions ~/.config/nemovideo/ but the registry entry did not; ask the author whether credentials are persisted there. (3) Prefer using an anonymous/limited token or a disposable account for testing, and do a trial with non-sensitive footage first. (4) Don’t set NEMO_TOKEN if that same token is used for other services you care about, and avoid granting other unrelated credentials. If you want higher assurance, request the skill author to provide a homepage, source or manifest that explains storage and retention of uploads and tokens.

Getting Started

Send me your raw video footage and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "edit a 2-minute event recording shot on a phone into a 1080p MP4"
• "trim the best moments and add background music"
• "editing raw footage into shareable video clips for content creators and marketers"

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.

EB Video — Edit and Export Video Clips

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

Say you have a 2-minute event recording shot on a phone and want to trim the best moments and add background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing eb video, 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.

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

Header	Value
X-Skill-Source	eb-video
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-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.

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

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)

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

Common Workflows

Quick edit: Upload → "trim the best moments and add background music" → 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 best moments and add background music" — 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.