← 返回 Skills 市场
peand-rover

Chatgpt Video Maker Free

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
60
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install chatgpt-video-maker-free
功能描述
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...
使用说明 (SKILL.md)

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 \x3CNEMO_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":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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=\x3Cid>, 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.

安全使用建议
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.
功能分析
Type: OpenClaw Skill Name: chatgpt-video-maker-free Version: 1.0.0 The skill bundle provides a functional interface for an AI video generation service hosted at nemovideo.ai. It includes detailed instructions for the agent to manage sessions, handle file uploads, and process video rendering tasks via a remote API. The use of environment variables (NEMO_TOKEN) and network communication is consistent with the stated purpose of the tool, and no indicators of data exfiltration, malicious execution, or unauthorized access were found in SKILL.md or _meta.json.
能力评估
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.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install chatgpt-video-maker-free
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /chatgpt-video-maker-free 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
ChatGPT Video Maker Free 1.0.0 — Initial Release - Instantly generate 1080p AI videos from 200-word product descriptions or blog posts using simple text prompts. - No manual editing: Drop your text prompt and get a finished video (MP4, MOV, GIF, etc.) in 1-2 minutes. - Seamless cloud workflow: Upload, process, and download — no local software or timeline editing required. - Free usage includes 100 credits and full-featured exports; no signup needed for basic access. - Automated session and token management with status feedback and clear error messages.
元数据
Slug chatgpt-video-maker-free
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Chatgpt Video Maker Free 是什么?

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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 60 次。

如何安装 Chatgpt Video Maker Free?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install chatgpt-video-maker-free」即可一键安装,无需额外配置。

Chatgpt Video Maker Free 是免费的吗?

是的,Chatgpt Video Maker Free 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Chatgpt Video Maker Free 支持哪些平台?

Chatgpt Video Maker Free 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Chatgpt Video Maker Free?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

💬 留言讨论