Maker Hindi

Turn a 60-second product clip or five product images into 1080p Hindi language videos just by typing what you need. Whether it's creating videos with Hindi t...

Security Scan

The skill's requests and runtime instructions are consistent with a cloud-based Hindi video creation service: it needs a NEMO_TOKEN and uploads user media to nemovideo.ai; nothing requested appears unrelated to making videos.

Purpose & Capability

Name/description (Hindi video creation) align with the skill's behavior: it posts uploads, creates render sessions, streams SSE, and returns download URLs. The single required env var (NEMO_TOKEN) is exactly the credential needed to call the backend API. One minor inconsistency: the SKILL.md frontmatter metadata lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths — likely harmless but worth noting.

Instruction Scope

The SKILL.md instructs the agent to: check/provision NEMO_TOKEN (by calling an anonymous-token endpoint if absent), create sessions, upload media, use SSE for edits, poll render status, and include attribution headers. Those actions are within the scope of a cloud render pipeline. Two items to be aware of: (1) it instructs the agent to read the skill's YAML frontmatter/version and to detect install path (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform — this requires inspecting local paths and may expose platform/install-location data even though it’s not needed for core media processing; (2) it will transmit user media and session tokens to an external domain (mega-api-prod.nemovideo.ai), which is expected for a cloud service but is a privacy/network operation you should accept consciously.

Install Mechanism

Instruction-only skill with no install step and no code files — lowest disk/write risk. There is no package download or archive extraction specified.

Credentials

Only NEMO_TOKEN is declared/used as a credential (and the skill can obtain a short-lived anonymous token if none is present). There are no unrelated secrets or broad credential requests. The frontmatter's mention of a config path is inconsistent with registry data and implies the skill might read ~/.config/nemovideo/ if present — this is not strictly necessary for operation and is a minor privacy consideration.

Persistence & Privilege

always:false and no install-time persistence actions are requested. The skill does not ask to modify other skills or global agent configuration. Autonomous invocation is allowed (default) but not excessive for this use case.

Assessment

This skill behaves like a normal cloud-based video creation integration: it will upload any media you give it and call endpoints on mega-api-prod.nemovideo.ai using a NEMO_TOKEN (you can provide one or the skill will request an anonymous short-lived token). Before installing, consider: 1) Do you trust nemovideo.ai to handle your media and metadata? Uploaded media, session IDs, and tokens are sent to that external service. 2) If you’re concerned about account linkage or data retention, provide your own NEMO_TOKEN from an account you control instead of allowing anonymous-token creation. 3) The skill reads its frontmatter and tries to detect the install path (which may reveal platform/install-location info) — if that’s a privacy concern, ask the author to remove that behavior. 4) There is no installer or local code, so disk risk is low, but network/privacy exposure is the primary consideration. If you want extra assurance, verify the service's privacy policy or test with non-sensitive media first.

Getting Started

Share your video clips or images and I'll get started on Hindi video creation. Or just tell me what you're thinking.

Try saying:

• "create my video clips or images"
• "export 1080p MP4"
• "create a Hindi promotional video with"

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.

Maker Hindi — Create Hindi Language Videos

This tool takes your video clips or images and runs Hindi video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 60-second product clip or five product images and want to create a Hindi promotional video with text overlays and voiceover — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 2 minutes produce the fastest Hindi video output.

Matching Input to Actions

User prompts referencing maker hindi, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
3. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: 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: maker-hindi
• 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.

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)

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "create a Hindi promotional video with text overlays and voiceover" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 for widest compatibility across Indian social platforms.

Common Workflows

Quick edit: Upload → "create a Hindi promotional video with text overlays 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.