Kapwing Free Text To Video

Turn a 150-word blog post summary into 1080p AI-generated videos just by typing what you need. Whether it's generating videos from written text or scripts or...

Security Scan

The skill mostly behaves like a cloud text→video connector, but there are several inconsistencies (name vs backend domain, declared vs actual config/env behavior) that don't add up and warrant caution before installing.

Purpose & Capability

The skill is named and marketed as a 'Kapwing' integration but all endpoints point to mega-api-prod.nemovideo.ai (not an obvious Kapwing domain) and the skill's source/homepage are unknown. That mismatch between branding and actual backend is suspicious and could be misleading. Also the registry declares NEMO_TOKEN as a required env var, yet the instructions provide a complete anonymous-token flow, which contradicts the 'required' designation.

Instruction Scope

SKILL.md clearly confines actions to contacting the specified API (session creation, SSE, uploads, render/polling, credits). It instructs the agent to detect install path to set an X-Skill-Platform header and to store session_id and token for subsequent requests. It also instructs not to show raw tokens to the user. These instructions are within a video-service integration's scope, but the install-path detection and the directive to hide API responses/token values are noteworthy — they broaden what the agent must read/store and could be used to obscure state if the backend is untrusted.

Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing is downloaded or written by an installer. That minimizes install-time risk.

Credentials

Only NEMO_TOKEN is declared as required, which is proportionate if the skill uses that service. However, the documentation shows the skill can obtain an anonymous NEMO token itself when NEMO_TOKEN is not present — making the 'required' designation misleading. Additionally, the YAML frontmatter in SKILL.md lists a config path (~/.config/nemovideo/) while the registry metadata earlier reported no required config paths; that mismatch is inconsistent and worth questioning.

Persistence & Privilege

The skill does not request always:true and does not claim system-wide modifications. It does instruct storing session state (session_id and derived tokens) for subsequent requests, which is normal for an API integration. Because the skill also references a config path in its metadata, confirm where session data is stored before installing.

What to consider before installing

This skill appears to be a cloud text→video connector but has several red flags: (1) the skill name ('Kapwing') doesn't match the API host (nemovideo.ai) — ask the author which service you're actually connecting to; (2) the registry says NEMO_TOKEN is required but the instructions include an anonymous token flow — clarify whether you must supply your own token or if the skill will create one for you; (3) SKILL.md mentions a config path (~/.config/nemovideo/) but registry metadata lists none — ask where session/token data will be stored and for how long. If you plan to provide any long-lived credentials, verify the backend domain, privacy policy, and who operates the endpoint before installing or supplying secrets.

Getting Started

Ready when you are. Drop your text prompt here or describe what you want to make.

Try saying:

• "convert a 150-word blog post summary into a 1080p MP4"
• "turn this text into a short video with visuals and captions"
• "generating videos from written text or scripts for content creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Kapwing Free Text to Video — Convert Text into Shareable Videos

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

Here's a typical use: you send a a 150-word blog post summary, ask for turn this text into a short video with visuals and captions, 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, clearer text produces more accurate and visually relevant video output.

Matching Input to Actions

User prompts referencing kapwing free text to video, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is kapwing-free-text-to-video, 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).

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.

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

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.

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

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)

Common Workflows

Quick edit: Upload → "turn this text into a short video with visuals and captions" → 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 "turn this text into a short video with visuals and captions" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.