Video Maker Renderforest

Skip the learning curve of professional editing software. Describe what you want — create a 30-second promo video using my logo and brand colors — and get br...

Security Scan

The skill's requirements and runtime instructions are coherent with a cloud video-rendering service: it asks for a single service token, describes the API calls it will make, and has no installable code — nothing appears disproportionate to the stated purpose.

Purpose & Capability

The skill is described as a cloud video rendering helper and requires only a single service token (NEMO_TOKEN), which is consistent. Minor mismatch: the SKILL.md frontmatter metadata includes a config path (~/.config/nemovideo/) but the registry metadata lists no required config paths; this is likely a bookkeeping inconsistency rather than malicious.

Instruction Scope

Instructions are narrowly focused on creating sessions, uploading media, running SSE-based generation, polling renders, and checking credits — all within the rendering backend. Two things to note: (1) upload instructions reference multipart file uploads by local file path (e.g., -F "files=@/path"), which implies the agent will need access to user-provided files or paths; ensure the agent/platform only supplies user-intended files and does not attempt to read arbitrary system files. (2) The runtime asks the agent to derive an X-Skill-Platform value by detecting install paths — this requires inspecting the agent environment/install location, which is benign for telemetry but worth awareness.

Install Mechanism

No install spec or code is included; the skill is instruction-only. That minimizes on-disk risk — the skill relies on outbound HTTP calls to the described backend.

Credentials

The only declared required credential is NEMO_TOKEN (primaryEnv), which matches a cloud rendering service. The SKILL.md also documents generating an anonymous token if NEMO_TOKEN is absent (by calling the service's anonymous-token endpoint) — expected for anonymous usage. There are no unrelated secrets requested. The earlier noted metadata mention of a config path (~/.config/nemovideo/) is not reflected in the registry requirements — a small inconsistency to be aware of.

Persistence & Privilege

The skill does not request always:true and has no install-time persistence. It does instruct keeping session_id for the running session, which is normal session behavior and not a platform-level privilege escalation.

Assessment

This skill appears to do what it claims: it calls a remote NemoVideo API to create sessions, upload user media, and return render URLs. Before installing or using it: (1) Confirm you trust the nemo video backend (https://mega-api-prod.nemovideo.ai) because all uploaded media and generated content will be sent to that service. (2) Only provide NEMO_TOKEN if it is specifically issued for this service; avoid supplying tokens or secrets for unrelated services. (3) When uploading files, ensure the agent/platform only uploads files you explicitly provide; do not let the skill attempt to read arbitrary filesystem paths. (4) Note the small metadata inconsistency (config path listed in SKILL.md but not in registry) — harmless but worth verifying with the skill author if you need strict provenance. If you need higher assurance, ask the publisher for a homepage or source repo and for details about data retention and privacy of uploaded media.

Getting Started

Send me your images, text, audio and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

• "create a logo, tagline text, and background music file into a 1080p MP4"
• "create a 30-second promo video using my logo and brand colors"
• "creating branded promo or intro videos from templates for marketers, small business owners, content creators"

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.

Video Maker Renderforest — Create Branded Videos From Templates

Send me your images, text, audio and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a logo, tagline text, and background music file, type "create a 30-second promo video using my logo and brand colors", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scripts and fewer scenes render significantly faster.

Matching Input to Actions

User prompts referencing video maker renderforest, 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is video-maker-renderforest, 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).

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.

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

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

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.

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 "create a 30-second promo video using my logo and brand colors" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, PNG, JPG for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "create a 30-second promo video using my logo and brand colors" → 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.