Transcribe Video To Text Free

Get plain text transcript ready to post, without touching a single slider. Upload your video files (MP4, MOV, AVI, WebM, up to 500MB), say something like "tr...

Security Scan

The skill's requirements and runtime instructions are internally consistent with a cloud video-transcription service: it asks for a single service token, describes API calls to a single domain, and does not request unrelated credentials or local file system access — but the skill has no source/homepage and declares a config path it never references, so exercise caution before trusting long-lived credentials or uploading sensitive videos.

Purpose & Capability

The name/description (video→text transcription) aligns with the declared NEMO_TOKEN credential and the SKILL.md which calls nemovideo.ai endpoints. Minor mismatch: frontmatter lists a config path (~/.config/nemovideo/) that the instructions never explicitly say to read; this is a small inconsistency but not a strong indicator of malicious intent.

Instruction Scope

SKILL.md confines operations to uploading user-supplied media and calling the nemovideo.ai API (session creation, upload, SSE, export/polling). It does require generating an anonymous token when NEMO_TOKEN is not present and storing session_id, but it does not instruct reading arbitrary local files or accessing unrelated environment variables. It does require adding attribution headers and 'auto-detecting' platform from an install path which may require the agent to inspect its environment/install location — this is reasonable for attribution but worth noting.

Install Mechanism

No install spec or code files are included (instruction-only skill). That minimizes on-disk write/execution risk.

Credentials

Only NEMO_TOKEN is required (primaryEnv). That is proportional for a third‑party transcription API. The skill also documents an anonymous-token flow if NEMO_TOKEN is missing. The declared config path is not used in the instructions — this should be clarified by the publisher. No other unrelated secrets are requested.

Persistence & Privilege

always is false and there's no install-time persistence or modifications to other skills or system-wide configs described. The skill stores short-lived session_id/token info for API calls, which is expected for this functionality.

Assessment

This skill appears to do what it says (upload your video to nemovideo.ai for transcription) and only asks for a single service token. Before installing or using it: - Remember uploads go to an external service (mega-api-prod.nemovideo.ai). Do not upload sensitive or confidential video unless you trust that domain and its privacy policy. - NEMO_TOKEN (if set in your environment) will be used directly; avoid placing long-lived or privileged credentials in environment variables unless necessary. Prefer the anonymous-token flow for occasional use. - The skill has no published source or homepage — lack of provenance increases risk. Consider asking the publisher for documentation, a privacy policy, or a canonical repo before trusting it. - The frontmatter mentions a local config path (~/.config/nemovideo/) but the instructions do not say to read it — clarify with the publisher whether the skill will access local config files. - If you need higher assurance, test with non-sensitive sample videos and inspect network/activity logs (or run in an isolated environment) before using with private content.

Getting Started

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

Try saying:

• "convert a 10-minute interview recorded on a smartphone into a 1080p MP4"
• "transcribe the spoken words into a text document"
• "converting spoken video content into editable text for students, journalists, content creators"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Transcribe Video to Text Free — Convert Video Speech to Text

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

Here's a typical use: you send a a 10-minute interview recorded on a smartphone, ask for transcribe the spoken words into a text document, 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 clips under 5 minutes produce faster and more accurate transcripts.

Matching Input to Actions

User prompts referencing transcribe video to text 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.

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.

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

Header	Value
X-Skill-Source	transcribe-video-to-text-free
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.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

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

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.

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

Common Workflows

Quick edit: Upload → "transcribe the spoken words into a text document" → 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 "transcribe the spoken words into a text document" — concrete instructions get better results.

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

MP4 files with clear audio yield the most accurate transcription results.