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Ai Video Editor Higgsfield

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-video-editor-higgsfield
功能描述
edit raw video footage into cinematic edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. TikTok creators and social media filmma...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "apply cinematic motion effects and smooth"

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.

AI Video Editor Higgsfield — Edit Videos with AI Motion Effects

Send me your raw video footage and describe the result you want. The AI video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 60-second raw clip shot on a smartphone, type "apply cinematic motion effects and smooth scene transitions like Higgsfield", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 30 seconds produce the most consistent AI motion results.

Matching Input to Actions

User prompts referencing ai video editor higgsfield, 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":"\x3Clang>"}. 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/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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.

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

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

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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=\x3Cid>, 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

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.

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)

Common Workflows

Quick edit: Upload → "apply cinematic motion effects and smooth scene transitions like Higgsfield" → 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 "apply cinematic motion effects and smooth scene transitions like Higgsfield" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest compatibility across social platforms.

安全使用建议
This skill appears to do what it says — it uploads your videos to mega-api-prod.nemovideo.ai and performs cloud-side editing, so expect your media (and any metadata in the files) to be transmitted to that service. Before installing: (1) confirm you trust the nemovideo endpoint and review its privacy/terms if you will upload sensitive footage; (2) avoid putting unrelated secrets into NEMO_TOKEN — only supply a token intended for this service (or let the skill obtain an anonymous token); (3) note the skill may check local install paths and read its own frontmatter for attribution (harmless but filesystem access); and (4) there is a small metadata inconsistency (frontmatter lists a config path while the registry summary did not) — you may ask the skill author to clarify what local config, if any, is required.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-higgsfield Version: 1.0.0 The skill is a legitimate integration for the Higgsfield AI video editing service (nemovideo.ai). It provides instructions for an AI agent to manage authentication via environment variables or anonymous tokens, handle file uploads, and interact with a remote GPU-based rendering pipeline. The behavior is consistent with the stated purpose, and there are no indicators of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
The name/description (AI video editing, cloud GPU rendering) align with the behavior in SKILL.md: creating sessions, uploading video files, starting render jobs, polling status, and returning download URLs. Requesting a service token (NEMO_TOKEN) and hitting mega-api-prod.nemovideo.ai is appropriate for that purpose.
Instruction Scope
Instructions stay inside the expected domain (session creation, upload, render, SSE). They explicitly instruct the agent to upload user-provided media to the remote API and to stream/poll job state. Two minor scope items to note: (1) the skill instructs reading its own YAML frontmatter for attribution (expected), and (2) it suggests detecting install platform by probing user paths like ~/.clawhub/ and ~/.cursor/skills/ — this requires simple filesystem checks and is attributable-only, but is not strictly necessary for editing. Overall not malicious, but you should be aware media will be transmitted off-device.
Install Mechanism
No install spec or code is included (instruction-only skill). That minimizes disk persistence risk — nothing is downloaded or executed locally by the skill instructions.
Credentials
The skill requires a single credential (NEMO_TOKEN) which is appropriate for an API-backed editor. SKILL.md also references a config path (~/.config/nemovideo/) in its frontmatter metadata; the registry summary showed 'Required config paths: none', so there is a small metadata inconsistency to be aware of. Do not place unrelated secrets in NEMO_TOKEN; it should be a token scoped to this service.
Persistence & Privilege
The skill is not marked always:true and does not request elevated persistence or modification of other skills/configs. Autonomous invocation is allowed (platform default) but there is no additional privilege requested.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ai-video-editor-higgsfield
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-higgsfield 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
AI Video Editor Higgsfield 1.0.0 — Initial Release - Launches cloud-based AI video editing for creators, supporting MP4, MOV, AVI, and WebM files up to 500MB. - Enables AI-driven cinematic effects and smooth motion edits, optimized for TikTok and social media clips. - Provides fast, server-side processing with 1080p MP4 output delivered in 1–2 minutes. - Integrates automatic session management and anonymous/free token acquisition for easy user onboarding. - Includes workflows for uploading, editing, exporting, and checking credits and project status.
元数据
Slug ai-video-editor-higgsfield
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Ai Video Editor Higgsfield 是什么?

edit raw video footage into cinematic edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. TikTok creators and social media filmma... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 89 次。

如何安装 Ai Video Editor Higgsfield?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-video-editor-higgsfield」即可一键安装,无需额外配置。

Ai Video Editor Higgsfield 是免费的吗?

是的,Ai Video Editor Higgsfield 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ai Video Editor Higgsfield 支持哪些平台?

Ai Video Editor Higgsfield 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ai Video Editor Higgsfield?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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