Text Video Generator

generate text prompts into ready-to-share videos with this text-video-generator skill. Works with TXT, DOCX, PDF, copied text files up to 500MB. marketers, c...

Security Scan

The skill's requests and runtime instructions are largely consistent with a cloud video-generation service, but there are a few small mismatches and privacy implications you should review before installing.

Purpose & Capability

The skill claims to convert text into videos and its runtime instructions only call a remote video-rendering API and upload user media — the single required credential (NEMO_TOKEN) and the described endpoints align with that purpose.

Instruction Scope

Instructions direct the agent to create an anonymous token if none is present, create sessions, upload user files (up to 500MB), stream SSE events, and poll for renders. All of these behaviors are appropriate for an online video-rendering service, but they do mean user content is uploaded to mega-api-prod.nemovideo.ai and an agent-run token/session is created automatically. The SKILL.md also instructs the agent to hide raw API responses and tokens from the user; this is sensible for token secrecy but reduces visibility into the backend interactions.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest-risk install surface. Nothing is downloaded or extracted by the skill itself.

Credentials

The only declared environment variable is NEMO_TOKEN (primaryEnv), which is appropriate. One inconsistency: the skill frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata shows no required config paths. That mismatch is minor but should be clarified. The skill can also obtain an anonymous token via the public API if NEMO_TOKEN is not set, meaning the user does not strictly need to supply credentials.

Persistence & Privilege

always:false and no install-time persistence are used. The SKILL.md instructs storing the session_id for requests, which is normal ephemeral session state. Nothing in the skill requests elevated or platform-wide privileges.

Assessment

This skill uploads user text and media to an external service (mega-api-prod.nemovideo.ai) and will create or use an NEMO_TOKEN to run render jobs. Before installing, confirm you trust that endpoint and are comfortable with your content being uploaded and processed there. If you prefer tighter control, supply your own NEMO_TOKEN (instead of allowing the skill to obtain an anonymous token) and avoid uploading sensitive files. Also ask the author to clarify the config-path mention (~/.config/nemovideo/) since the registry metadata does not list any required config paths.

Getting Started

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

Try saying:

• "generate a 150-word product description into a 1080p MP4"
• "turn this blog paragraph into a 30-second video with visuals and background music"
• "generating videos from written content or scripts for marketers, content creators, educators"

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 Video Generator — Turn Text Into Shareable Videos

Drop your text prompts in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 150-word product description, ask for turn this blog paragraph into a 30-second video with visuals and background music, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter, clearer text produces more accurate visuals — aim for one idea per sentence.

Matching Input to Actions

User prompts referencing text video generator, 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.

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

Header	Value
X-Skill-Source	text-video-generator
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.

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

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says	You do
"click [button]" / "点击"	Execute via API
"open [panel]" / "打开"	Query session state
"drag/drop" / "拖拽"	Send edit via SSE
"preview in timeline"	Show track summary
"Export button" / "导出"	Execute 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 → "turn this blog paragraph into a 30-second video with visuals and background music" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this blog paragraph into a 30-second video with visuals and background music" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, copied text for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and presentations.