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Free Maker Text

v1.0.0

Get text-based videos ready to post, without touching a single slider. Upload your text prompts (TXT, DOCX, PDF, MP4, up to 200MB), say something like "turn...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dsewell-583h0/free-maker-text.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Free Maker Text" (dsewell-583h0/free-maker-text) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/free-maker-text
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install free-maker-text

ClawHub CLI

Package manager switcher

npx clawhub@latest install free-maker-text
Security Scan
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
Name/description claim remote AI video rendering; SKILL.md instructs calls to a Nemovideo API and file uploads (TXT/DOCX/PDF/MP4) — this is coherent. Minor mismatch: registry metadata earlier said no required config paths, while the SKILL.md YAML metadata lists ~/.config/nemovideo/ (inconsistent).
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Instruction Scope
Instructions direct the agent to obtain or use a bearer token, create sessions, upload user files, stream SSE messages, poll render status, and download produced media — all expected for a cloud render service. However these steps will transmit user data (including uploaded documents and videos) to an external domain (mega-api-prod.nemovideo.ai). The skill explicitly instructs generating an anonymous token and persisting session_id/token (it warns not to print them). Ensure you consent to third‑party uploads and storage.
Install Mechanism
Instruction-only skill with no install spec and no code files — low install risk (nothing written or executed locally by an installer).
Credentials
Only one env var (NEMO_TOKEN) is declared and used, which fits the service. The SKILL.md also documents generating an anonymous token if NEMO_TOKEN is not present. The YAML frontmatter mentions a config path (~/.config/nemovideo/), but the registry summary listed none — this inconsistency should be clarified.
Persistence & Privilege
always:false and no requests to modify other skills or system-wide configs. The skill asks to save session tokens (normal for API clients) but does not request elevated system privileges.
What to consider before installing
This skill calls a third‑party API (mega-api-prod.nemovideo.ai) and will upload whatever files you provide (text docs, media) for server-side rendering. Before installing, verify the service’s identity and privacy terms, and avoid uploading sensitive secrets or proprietary content. Note the small metadata inconsistency (SKILL.md references ~/.config/nemovideo/ while registry said none) — ask the publisher which config/data is stored locally. Prefer to set your own NEMO_TOKEN if you have one rather than relying on anonymous-token generation. If you need stronger assurance, request the publisher’s homepage, privacy policy, or an official API documentation link; that information would raise confidence.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

📝 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97993df6sfer3dpg8h25ezma9858skm
87downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

Share your text prompts and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my text prompts"
  • "export 1080p MP4"
  • "turn this text into a 30-second"

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.

Free Maker Text — Convert Text Into Videos

Send me your text prompts and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a short paragraph describing a product launch, type "turn this text into a 30-second video with visuals and background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter text inputs under 100 words produce the most focused and accurate video output.

Matching Input to Actions

User prompts referencing free maker text, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-maker-text, 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.

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

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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 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)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Common Workflows

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

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 background music" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and presentation tools.

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