Free Free Text

convert text prompts into text-based videos with this skill. Works with TXT, DOCX, PDF, plain text files up to 200MB. content creators use it for converting...

Security Scan

The skill's declared purpose (convert text to video) matches the network calls and token usage, but there are inconsistencies and some runtime behaviors (filesystem probing, anonymous token flow to an unknown backend, missing source/homepage) that warrant caution before installing.

Purpose & Capability

The skill claims to convert text into videos and all of its runtime instructions are focused on calling a remote video-rendering API — requiring a NEMO_TOKEN or an anonymous token is consistent. However, the SKILL.md metadata asks the agent to check a config path (~/.config/nemovideo/) and to detect install path for attribution headers; the registry metadata shown earlier listed no required config paths. This mismatch (registry vs SKILL.md) is unexplained and worth questioning.

Instruction Scope

Instructions include network calls to mega-api-prod.nemovideo.ai (expected for a cloud service) and explicit upload endpoints for user files (consistent with functionality). But the skill also directs the agent to: read this file's YAML frontmatter at runtime, detect the agent install path (~/.clawhub, ~/.cursor/skills/, else unknown) to set X-Skill-Platform, and possibly access ~/.config/nemovideo/. Those filesystem reads are outside the core task of converting uploaded text and are not declared consistently in the registry metadata — this is scope creep that could expose more local context than users expect.

Install Mechanism

No install spec and no code files (instruction-only) means nothing is written to disk by the skill itself — this is low-risk from an install perspective. The runtime behavior is purely API calls and file uploads.

Credentials

Only one credential is requested (NEMO_TOKEN), and the skill provides a clear anonymous-token fallback. Requesting a service token is proportionate to calling a third-party API. That said, the skill's anonymous-token flow requires generating a UUID and posting it to the service (transmitting a client identifier) and the skill insists that Authorization and custom attribution headers be sent on every request; users should understand these headers and what they reveal. No unrelated credentials are requested.

Persistence & Privilege

The skill is not always-enabled and does not request elevated platform privileges. It can be invoked autonomously (platform default), which increases blast radius but is not in itself unusual. The skill does note that session tokens can orphan render jobs if the user disconnects — an expected behavior for remote render jobs.

What to consider before installing

Before installing, confirm the backend and author: ask for the skill's source repository or homepage and a privacy policy for mega-api-prod.nemovideo.ai. If you plan to upload private documents, understand that files will be sent to that remote API and that an anonymous client id is created if you don't supply a token. Ask the author why the skill needs to read ~/.config/nemovideo/ and to probe install paths — this is not strictly necessary for simple text-to-video conversion. Prefer skills with a verifiable backend and published code; if you proceed, avoid supplying system-level or unrelated credentials, consider running the skill in a sandboxed environment, and monitor outgoing network traffic or use an allowlist to restrict where files/credentials can be sent.

Getting Started

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

Try saying:

• "convert a plain text description of a product launch into a 1080p MP4"
• "turn this text into a 30-second video with visuals and music"
• "converting written content into shareable videos for content creators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Free Free Text — Convert Text Into Videos

Drop your text prompts 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 plain text description of a product launch, ask for turn this text into a 30-second video with visuals and music, 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 and clearer text prompts produce more accurate video results.

Matching Input to Actions

User prompts referencing free free text, 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.

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

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

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

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.

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 "turn this text into a 30-second video with visuals and music" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "turn this text into a 30-second video with visuals and music" → 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.