Text To Video Explainer Ai

Skip the learning curve of professional editing software. Describe what you want — turn this script into an animated explainer video with voiceover and subti...

Security Scan

The skill's declared purpose (turn text/scripts into explainer videos) matches what its instructions do; it talks to a single backend service and only asks for a single service token, but there are minor metadata/instruction inconsistencies you should be aware of before installing.

Purpose & Capability

The name/description (text→video explainer) align with the required credential (NEMO_TOKEN) and the documented API endpoints on mega-api-prod.nemovideo.ai. The skill's network activity (uploading scripts/media, render/export endpoints, credits check) is expected for this functionality.

Instruction Scope

SKILL.md instructs the agent to obtain or use a NEMO_TOKEN, create a session, upload files, stream SSE responses, and poll render status — all consistent with a cloud render pipeline. It also directs the agent to read its own YAML frontmatter for attribution and to detect an install path string for a header. Those actions are limited to the skill itself and the documented backend; there are no instructions to read unrelated system files or unrelated environment variables. The frontmatter also mentions a local config path (~/.config/nemovideo/), but the runtime steps do not clearly justify inspecting or using that directory.

Install Mechanism

This is instruction-only with no install spec or third-party downloads, so nothing is written to disk by an installer — lowest risk for install mechanism.

Credentials

Only one credential (NEMO_TOKEN) is declared as the primary credential, which is reasonable for a single-service integration. However, SKILL.md also explains how to automatically obtain an anonymous token if NEMO_TOKEN is not set — this makes the credential effectively optional despite registry metadata listing it as required. The frontmatter references a config path (~/.config/nemovideo/) that is not declared in the registry's required config paths, creating a small metadata inconsistency.

Persistence & Privilege

The skill is not marked always:true and does not request system-wide privileges. It asks to store a session_id for subsequent API calls (normal session state) but does not request long-term or cross-skill configuration changes.

Assessment

This skill appears to do what it says: upload your script/media to the nemovideo.ai backend, create a temporary session, and return a rendered video. Before installing, consider: (1) You will be sending your text and any uploaded files to mega-api-prod.nemovideo.ai — verify you are comfortable sharing that content and check the service's privacy/data retention policy. (2) The registry metadata and the SKILL.md disagree slightly: the registry marks NEMO_TOKEN as required but the skill can obtain an anonymous token automatically; decide whether you prefer setting your own token or allowing the skill to request an anonymous one. (3) The frontmatter mentions a local config path (~/.config/nemovideo/) and asks to read YAML frontmatter for attribution — this is limited and not high risk, but be aware the skill may read its own metadata and detect install path strings. If you need stronger guarantees, ask the skill author for a privacy policy or a link to the service's terms and to clarify whether any local files will be accessed.

Getting Started

Share your text script and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

• "convert my text script"
• "export 1080p MP4"
• "turn this script into an animated"

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.

Text to Video Explainer AI — Convert Scripts into Explainer Videos

Send me your text script 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 200-word product explainer script, type "turn this script into an animated explainer video with voiceover and subtitles", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scripts under 150 words produce tighter, more focused explainer videos.

Matching Input to Actions

User prompts referencing text to video explainer ai, 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: text-to-video-explainer-ai
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this script into an animated explainer video with voiceover and subtitles" — concrete instructions get better results.

Max file size is 50MB. Stick to TXT, DOCX, PDF, SRT for the smoothest experience.

Export as MP4 for widest compatibility across YouTube, LinkedIn, and presentations.

Common Workflows

Quick edit: Upload → "turn this script into an animated explainer video with voiceover and subtitles" → 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.