Ai Data Format Converter

Skip the learning curve of professional editing software. Describe what you want — convert this CSV to JSON and wrap it in a video data visualization export...

Security Scan

The skill's requests and runtime instructions are coherent with a cloud-based data-format-and-video conversion service and do not ask for unrelated credentials or invasive local access.

Purpose & Capability

Name/description promise (convert data formats and produce video exports) matches the SKILL.md: it describes a cloud backend API for session creation, upload, render and export. The single required env var (NEMO_TOKEN) and config path (~/.config/nemovideo/) are consistent with a cloud service client.

Instruction Scope

Runtime instructions focus on authenticating, creating sessions, uploading user-provided files, sending SSE messages, polling renders and returning download URLs. There are no instructions to read unrelated local files, harvest other env vars, or exfiltrate system data beyond user files required for conversion.

Install Mechanism

No install spec or code files are present (instruction-only). This minimizes disk write/execution risk; network calls to the named API host are expected for a cloud service.

Credentials

Only NEMO_TOKEN is declared as required (primary credential) and the SKILL.md uses it for Bearer auth; no unrelated secrets or multiple credentials are requested. The skill also supports obtaining an anonymous token from its backend if none is present.

Persistence & Privilege

always is false and the skill does not request or instruct changes to other skills or system-wide config. It may detect install paths to populate an attribution header, which is limited scope and not privileged.

Assessment

This skill sends any files you provide to a third-party backend (mega-api-prod.nemovideo.ai) for processing and will use a NEMO_TOKEN (either provided by you or obtained anonymously) to authenticate. If you plan to upload sensitive data, verify the service's privacy/security posture first. The skill does not request other system credentials or write/install software, but it will upload files (up to 200MB) and make network requests. If you prefer, supply your own NEMO_TOKEN rather than allowing anonymous token creation, and revoke tokens/accounts when no longer needed.

Getting Started

Send me your data files and I'll handle the AI format conversion. Or just describe what you're after.

Try saying:

• "convert a CSV data file with 500 rows into a 1080p MP4"
• "convert this CSV to JSON and wrap it in a video data visualization export"
• "converting data files between formats for video pipeline workflows for developers, data analysts, video producers"

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.

AI Data Format Converter — Convert and Export Data Formats

Send me your data files and describe the result you want. The AI format conversion runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a CSV data file with 500 rows, type "convert this CSV to JSON and wrap it in a video data visualization export", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: smaller files with clean structure convert faster and with fewer errors.

Matching Input to Actions

User prompts referencing ai data format converter, 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 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-data-format-converter, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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

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.

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 "convert this CSV to JSON and wrap it in a video data visualization export" — concrete instructions get better results.

Max file size is 200MB. Stick to CSV, JSON, XML, MP4 for the smoothest experience.

Export as MP4 for widest compatibility when embedding converted data visuals.

Common Workflows

Quick edit: Upload → "convert this CSV to JSON and wrap it in a video data visualization export" → Download MP4. Takes 20-40 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.