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Highlight Editor Hd

v1.0.0

create raw video footage into HD highlight reels with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. sports creators, event videographers, cont...

0· 70·0 current·0 all-time

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/highlight-editor-hd.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Highlight Editor Hd" (dsewell-583h0/highlight-editor-hd) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/highlight-editor-hd
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 highlight-editor-hd

ClawHub CLI

Package manager switcher

npx clawhub@latest install highlight-editor-hd
Security Scan
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Purpose & Capability
The skill claims to render video highlights on cloud GPUs and requires a single API token (NEMO_TOKEN) and a nemovideo config path — this is consistent with a cloud video processing service. However, the SKILL.md also instructs detecting an agent install path (e.g., ~/.clawhub/ or ~/.cursor/skills/) to populate X-Skill-Platform headers, which is not clearly necessary for core functionality and could expose local install layout.
!
Instruction Scope
Instructions contain normal API flows (session creation, SSE, multipart upload) and an anonymous-token fallback if NEMO_TOKEN is absent. They also require inclusion of custom attribution headers and state that X-Skill-Platform is detected from local install paths — this implies the agent should inspect filesystem paths or runtime environment beyond the single declared env var. Uploading user video files to an external API is expected, but the install-path detection and automatic transmission of platform/paths risks unnecessary local information leakage.
Install Mechanism
There is no install spec and no code files; the skill is instruction-only, so nothing is written to disk by the skill itself. This is the lowest-risk install mechanism.
Credentials
The only required env var is NEMO_TOKEN (declared as primaryEnv) which is appropriate for a third-party API. The metadata also lists a config path (~/.config/nemovideo/) which is consistent. Minor mismatch: SKILL.md expects detection of other install paths for platform headers but those paths are not listed in required configPaths; this is an unexplained extra data point the agent would need to access.
Persistence & Privilege
The skill does not request always:true and does not indicate modifying other skills or system-wide settings. Autonomous invocation (default) is allowed but not, by itself, a flag — only relevant in combination with other concerns.
What to consider before installing
This skill appears to do what it says — it uploads user-supplied video files to nemovideo.ai and returns rendered MP4s — but check a few things before installing or using it: - Data exposure: Uploaded videos will be sent to an external service (https://mega-api-prod.nemovideo.ai). Do not upload sensitive or private recordings unless you trust that service and have reviewed its privacy/retention policies. - Environment token: NEMO_TOKEN is the only credential requested; treat it like any API secret. Avoid reusing a high-privilege token and consider using a dedicated token with limited scope. - Local-info leak: The skill instructs sending X-Skill-Platform derived from local install paths (e.g., ~/.clawhub/). Ask the developer to confirm what local paths will be inspected and to avoid sending full filesystem paths — this can leak information about your environment. Prefer a sanitized platform string rather than raw path inspection. - Anonymous fallback: If no NEMO_TOKEN is present, the skill will obtain an anonymous token from the external API. That behaviour is reasonable but means work may proceed under an externally-issued short-lived token; check what data is associated with anonymous sessions. - Confirm headers and attribution: The skill says missing attribution headers will cause export to fail with 402. Request clarification why these headers are required and whether they can be minimal to avoid sending unnecessary agent/system metadata. If you need higher assurance, ask the publisher for the skill's source code or for a privacy/security statement. If you cannot confirm how local paths are determined or sanitized, be cautious about installing or running the skill in environments containing sensitive files or secrets.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk979f2kscxm4w42m27d6pe1mxn84mk68
70downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Share your raw video footage and I'll get started on AI highlight extraction. Or just tell me what you're thinking.

Try saying:

  • "create my raw video footage"
  • "export 1080p MP4"
  • "extract the best moments and compile"

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.

Highlight Editor HD — Extract and Export HD Highlights

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI highlight extraction on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-hour sports game recording, ask for extract the best moments and compile them into a 3-minute highlight reel, 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 — trimming your source video to the relevant section before uploading speeds up highlight detection.

Matching Input to Actions

User prompts referencing highlight editor hd, 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 highlight-editor-hd, 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.

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.

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 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)

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 → "extract the best moments and compile them into a 3-minute highlight reel" → 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 "extract the best moments and compile them into a 3-minute highlight reel" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, MKV for the smoothest experience.

Export as MP4 with H.264 codec for the best balance of quality and file size.

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