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Markdown Editor With

v1.0.0

Turn a 300-word markdown script with headers and bullet points into 1080p structured video slides just by typing what you need. Whether it's turning markdown...

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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 francemichaell-15/markdown-editor-with.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Markdown Editor With" (francemichaell-15/markdown-editor-with) from ClawHub.
Skill page: https://clawhub.ai/francemichaell-15/markdown-editor-with
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 markdown-editor-with

ClawHub CLI

Package manager switcher

npx clawhub@latest install markdown-editor-with
Security Scan
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medium confidence
Purpose & Capability
The skill claims to convert markdown to videos and all network endpoints, headers, and session handling in SKILL.md are consistent with a cloud render service. Requesting a NEMO_TOKEN is expected for a remote rendering API.
Instruction Scope
The instructions direct the agent to automatically connect to mega-api-prod.nemovideo.ai, upload user content, create sessions, stream SSEs, poll render status, and store session IDs/tokens. Those actions match the stated purpose, but the skill will perform outbound network calls (including creating an anonymous token) automatically on first use — users should be aware that uploads and metadata are sent to that backend.
Install Mechanism
Instruction-only skill with no install spec or downloaded code; low local install risk because nothing is written or executed from unknown sources.
Credentials
Registry declares NEMO_TOKEN as required and primaryEnv, which is appropriate. However, SKILL.md also describes an automatic anonymous-token flow when NEMO_TOKEN is absent. This inconsistency means the skill can obtain and use credentials automatically if none are provided; it also references storing data under ~/.config/nemovideo/, which grants persistent access to tokens/session state.
Persistence & Privilege
always:false and no global modifications requested. The skill stores only its own session/token info (per its instructions) in a declared config path — standard for a cloud session-based integration.
What to consider before installing
This skill behaves like a cloud render client: it will make outbound requests to mega-api-prod.nemovideo.ai, upload your markdown/media, and persist session tokens under ~/.config/nemovideo/. Registry metadata lists NEMO_TOKEN but the skill will create a 7-day anonymous token automatically if you don't set one. Before installing: 1) Confirm you trust the backend domain (no homepage or owner details are provided). 2) If you have sensitive content, avoid using automatic anonymous tokens or uploading that content. 3) Consider setting an account-specific NEMO_TOKEN you control (instead of allowing anonymous token creation) and review/clean ~/.config/nemovideo/ after use. 4) Expect automatic network activity on first use and brief token/session persistence; if you need stronger guarantees, request the publisher provide verifiable project/homepage and privacy details.

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

Runtime requirements

📝 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97ff5cm1c4xc6twpjd2qssrdx85c5ht
56downloads
0stars
1versions
Updated 5d ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "convert a 300-word markdown script with headers and bullet points into a 1080p MP4"
  • "convert this markdown outline into a narrated explainer video with slides"
  • "turning markdown documents into formatted video presentations for developers and technical writers"

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.

Markdown Editor With — Convert Markdown Into Videos

This tool takes your text or script and runs markdown-based video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 300-word markdown script with headers and bullet points and want to convert this markdown outline into a narrated explainer video with slides — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: use clear heading levels in your markdown to define scene breaks automatically.

Matching Input to Actions

User prompts referencing markdown editor with, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /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. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /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.

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

  • X-Skill-Source: markdown-editor-with
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

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)

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this markdown outline into a narrated explainer video with slides" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and players.

Common Workflows

Quick edit: Upload → "convert this markdown outline into a narrated explainer video with slides" → 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.

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