Video To Text Gratis

convert video files into transcribed text files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. students, content creators, journalists us...

Security Scan

The skill's declared requirements and runtime instructions are internally consistent with a cloud video→text transcription service, but it will transmit uploaded videos and session tokens to an external backend and the package metadata has small inconsistencies and no public provenance — review before sending sensitive files.

Purpose & Capability

The name/description (video→text transcription) align with the required credential (NEMO_TOKEN) and the SKILL.md which documents HTTP APIs for uploading videos, creating sessions, polling render status, and getting transcripts/exports. Requesting a token for a cloud backend is expected for this purpose.

Instruction Scope

Instructions explicitly direct the agent to read NEMO_TOKEN, create sessions, upload files (multipart or by URL), use SSE for streaming responses, and poll render endpoints. These are coherent for a remote transcription/render service. Notably, the skill also instructs the agent to detect install path and read its own YAML frontmatter for attribution headers; that requires checking local paths (e.g. ~/.clawhub/, ~/.cursor/) and may touch a config path declared in the frontmatter (~/.config/nemovideo/) — this is not essential to core transcription and is an ancillary behavior to be aware of. All user-provided video data will be sent to mega-api-prod.nemovideo.ai as part of normal operation.

Install Mechanism

There is no install spec and no code files — the skill is instruction-only. That minimizes on-disk installation risk; runtime behavior is limited to making network calls and reading environment/files as described.

Credentials

Only one credential is declared (NEMO_TOKEN), which matches the backend usage. The SKILL.md also documents an anonymous-token flow (POST to the backend to obtain a temporary token if NEMO_TOKEN is not present), which is coherent but means the skill can obtain and use short-lived credentials itself. The frontmatter mentions a config path (~/.config/nemovideo/) that the registry metadata did not list — a minor inconsistency that means the skill may read that directory if present.

Persistence & Privilege

The skill is not force-installed (always: false) and has no install actions. It does not request system-wide privileges or modify other skills. Autonomous invocation is enabled by default but is not combined with other high-risk flags.

Assessment

This skill implements a cloud-based transcription/render pipeline: uploading a video will send the file to mega-api-prod.nemovideo.ai and the service will return transcripts and exported MP4s. Before installing or using it, consider: (1) privacy — do not upload sensitive or confidential videos unless you trust the unknown service owner (no homepage/provenance provided); (2) token handling — the skill will use NEMO_TOKEN if present or request an anonymous token from the backend (it can obtain short-lived credentials itself); (3) local file access — it may read certain local paths (its frontmatter references ~/.config/nemovideo/ and asks to detect install path) though no installer runs; (4) data retention and terms — confirm how uploaded media and transcripts are stored/retained by the backend. If you need stronger guarantees, prefer a local transcription tool or ask the skill author for a public homepage, privacy/retention policy, and source code so you can audit the service.

Getting Started

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

Try saying:

• "convert a 3-minute interview recorded on a smartphone into a 1080p MP4"
• "transcribe this video to text for free"
• "converting spoken video content into written transcripts for students, content creators, journalists"

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.

Video to Text Gratis — Convert Video Speech to Text

Send me your video files and describe the result you want. The AI transcription generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute interview recorded on a smartphone, type "transcribe this video to text for free", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 5 minutes produce the most accurate transcripts.

Matching Input to Actions

User prompts referencing video to text gratis, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

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

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

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)

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 "transcribe this video to text for free" — concrete instructions get better results.

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

Upload as MP4 for the fastest and most reliable transcription results.

Common Workflows

Quick edit: Upload → "transcribe this video to text for free" → Download MP4. Takes 30-60 seconds 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.