Chatgpt Video Maker Free

Turn a 200-word product description or blog post into 1080p AI-generated videos just by typing what you need. Whether it's generating videos from text prompt...

Security Scan

The skill's stated goal (turn text into videos) matches its network API usage, but there are metadata/instruction inconsistencies and a few behaviors (auto-detecting install path, referencing a local config path) that are unexplained and could cause the agent to read local files or environment data beyond what's needed.

Purpose & Capability

The skill's name and description (AI video generation) align with the API endpoints and workflows in SKILL.md (session creation, SSE generation, upload, render/export). Requesting a NEMO_TOKEN is reasonable for a video service. However, the SKILL.md frontmatter includes a config path (~/.config/nemovideo/) which the registry metadata earlier did not list — this mismatch merits scrutiny.

Instruction Scope

Runtime instructions explicitly tell the agent to use NEMO_TOKEN if present or obtain an anonymous token, create sessions, upload files (multipart with local file paths), handle SSE, and poll render endpoints. These are expected for a cloud rendering workflow. Concerns: (1) the SKILL.md asks to auto-detect the install path to set X-Skill-Platform (this implies inspecting the agent's filesystem/environment), and (2) the frontmatter's configPaths suggests reading ~/.config/nemovideo/ — neither of these accesses are clearly necessary for generating a video and were not declared in the registry metadata. The agent may therefore be directed to read local paths or other environment data beyond the single declared env var.

Install Mechanism

No install spec and no code files — instruction-only. This minimizes risk from arbitrary downloads or executable installs.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which is proportional for a remote API service. However, the SKILL.md also implies access to a local config path (~/.config/nemovideo/) and suggests auto-detecting install path for a header value; those additional local accesses were not declared in the top-level "Required config paths" and thus are unexpected.

Persistence & Privilege

The skill is not always-included and does not request elevated or persistent system-level privileges. It is allowed to be invoked autonomously (disable-model-invocation=false), which is normal for skills and not flagged on its own.

What to consider before installing

This skill largely behaves like a remote video-rendering integration and only needs a NEMO_TOKEN to call the service, but there are a few unexplained items you should consider before installing: 1) Origin and trust — the skill's source/homepage are missing; confirm who runs mega-api-prod.nemovideo.ai and whether you trust that provider. 2) Local file and config access — SKILL.md suggests auto-detecting an install path and references ~/.config/nemovideo/ even though the registry metadata didn't declare that; avoid providing access to local config directories unless you understand why. 3) Token scope — only give a NEMO_TOKEN that is limited in scope (or use the anonymous token flow) and avoid placing long-lived credentials in shared environments. 4) File uploads — the skill will upload files you provide; don't upload sensitive documents or secrets. 5) Verify headers and telemetry — the skill requires custom attribution headers; confirm you are comfortable with that identifying metadata being sent. If you need higher assurance, ask the publisher for source code or an official homepage, or request that the skill be updated to remove the undocumented configPath and to explicitly document any filesystem reads the agent will perform.

Getting Started

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

Try saying:

• "generate a 200-word product description or blog post into a 1080p MP4"
• "turn this text into a 60-second video with visuals and voiceover"
• "generating videos from text prompts without manual editing for content creators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

ChatGPT Video Maker Free — Generate Videos from Text Prompts

Send me your text prompts 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 description or blog post, type "turn this text into a 60-second video with visuals and voiceover", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter, clearer prompts produce more accurate and focused video results.

Matching Input to Actions

User prompts referencing chatgpt video maker free, 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.

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

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

Header	Value
X-Skill-Source	chatgpt-video-maker-free
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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

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 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 text into a 60-second video with visuals and voiceover" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across YouTube, TikTok, and Instagram.

Common Workflows

Quick edit: Upload → "turn this text into a 60-second video with visuals and voiceover" → 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.