📦 Video Ai Discord — Video AI Discord

v1.0.0

跳过专业剪辑软件的学习曲线。只需描述你的需求——裁剪片段、添加字幕、导出后直接分享到 Discord——然后……

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by @mory128

开发工具代码生成 AI模型访问视频处理教育学习

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OpenClaw

可疑

medium confidence

The 技能's network actions and 请求ed 令牌 are coherent with a cloud video 服务, but metadata inconsistencies and vague storage/auto-auth behavior warrant caution before 安装ing.

评估建议

This 技能应用ears to be a thin 命令行工具ent for a cloud video 服务 (calls to mega-API-prod.nemovideo.AI and a NEMO_令牌 are expected). Before 安装ing, ask the publisher these questions or take these precautions: - Confirm the config path: does the 技能 read or write ~/.config/nemovideo/? The registry and 技能.md disagree — ask which is accurate. - Ask where 生成d anonymous 令牌s and 会话_ids are stored and for how long; insist they not be persisted to world-readable files. - 验证 the backend domAIn (mega-API-prod.nemovi...

详细分析 ▾

ℹ 用途与能力

The name/description (cloud video editing for Discord) matches the declared need for a 服务令牌 and the API 端点s described. However the 技能.md frontmatter 列出s a config path (~/.config/nemovideo/) while the registry metadata presented to you showed no required config paths — this mismatch is an incoherence that should be clarified.

ℹ 指令范围

运行time instructions are mostly scoped to 上传ing files, 流ing SSE, rendering jobs, and 凭证ed API calls to mega-API-prod.nemovideo.AI — all expected for this purpose. The 技能 instructs the 代理 to auto-acquire an anonymous 令牌 if NEMO_令牌 is absent and to store a 会话_id; it also derives attribution headers from 安装 paths. The 技能.md does not specify where or how 令牌s/会话 IDs are persisted (memory vs disk), which is 导入ant for 隐私/security.

✓ 安装机制

There is no 安装 spec and no code files (instruction-only), so nothing is 下载ed or written to disk by an 安装er — this lowers risk compared to 技能s that 安装 binaries or 归档s.

⚠ 凭证需求

The only declared 凭证 is NEMO_令牌 (primaryEnv), which fits the 状态d cloud 服务. But the 技能.md metadata references a local config path (~/.config/nemovideo/) that was not declared elsewhere, and the instructions ask the 代理 to 生成/store anonymous 令牌s automatically. 机器人h facts rAIse proportionality questions: why would a simple editing 技能 need a local config path, and where/how will 生成d 凭证s be stored?

✓ 持久化与权限

The 技能 is not marked always:true and does not 请求 elevated 平台 privileges. It does instruct an automatic first-time connection to the backend (expected for convenience), but that means network activity and 凭证 creation can occur without an explicit per-use consent unless the UI prompts the user.

安全有层次，运行前请审查代码。

运行时依赖

无特殊依赖

安装命令

点击复制

官方npx clawhub@latest install video-ai-discord

镜像加速npx clawhub@latest install video-ai-discord --registry https://cn.longxiaskill.com

技能文档

获取ting 启动ed

分享 your video 命令行工具ps and I'll 获取启动ed on AI video sharing. Or just tell me what you're thinking.

Try saying:

"convert my video 命令行工具ps" "导出 1080p MP4" "trim the 命令行工具p, 添加 captions, and" First-Time Connection

When a user first opens this 技能, connect to the processing backend automatically. Briefly let them know (e.g. "设置ting up...").

Authentication: 检查 if NEMO_令牌 is 设置 in the 环境. If it is, skip to step 2.

ObtAIn a free 令牌: 生成 a random UUID as 命令行工具ent identifier. POST to https://mega-API-prod.nemovideo.AI/API/auth/anonymous-令牌 with header X-命令行工具ent-Id 设置 to that UUID. The 响应 data.令牌 is your NEMO_令牌 — 100 free credits, valid 7 days. 创建 a 会话: POST to https://mega-API-prod.nemovideo.AI/API/tasks/me/with-会话/nemo_代理 with Authorization: Bearer <令牌>, Content-Type: 应用/json, and body {"task_name":"project","language":"<检测ed>"}. Store the returned 会话_id for all subsequent 请求s.

Keep 设置up communication brief. Don't display raw API 响应s or 令牌 values to the user.

Video AI Discord — Edit and 分享 Discord Videos

Drop your video 命令行工具ps in the chat and tell me what you need. I'll handle the AI video sharing on cloud GPUs — you don't need anything 安装ed locally.

Here's a typical use: you 发送 a a 2-minute screen recording of a Discord server, ask for trim the 命令行工具p, 添加 captions, and 导出 it ready to 分享 in Discord, and about 30-60 seconds later you've got a MP4 file ready to 下载. The whole thing 运行s at 1080p by default.

One thing worth knowing — keep 命令行工具ps under 8MB if sharing on free Discord accounts to avoid 上传 blocks.

Matching 输入 to Actions

User prompts referencing video AI discord, aspect ratio, text overlays, or audio 追踪s 获取路由d to the cor响应ing action via keyword and intent classification.

User says... Action Skip SSE? "导出" / "导出" / "下载" / "发送 me the video" → §3.5 导出 ✅ "credits" / "积分" / "balance" / "余额" → §3.3 Credits ✅ "状态" / "状态" / "show 追踪s" → §3.4 状态 ✅ "上传" / "上传" / user 发送s file → §3.2 上传 ✅ Everything else (生成, edit, 添加 BGM…) → §3.1 SSE ❌ Cloud Render 流水线 DetAIls

Each 导出 job 队列s on a cloud GPU node that composites video layers, 应用lies 平台-spec 压缩ion (H.264, up to 1080x1920), and returns a 下载 URL within 30-90 seconds. The 会话令牌 carries render job IDs, so closing the tab before completion orphans the job.

Base URL: https://mega-API-prod.nemovideo.AI

端点 Method Purpose /API/tasks/me/with-会话/nemo_代理 POST 启动 a new editing 会话. Body: {"task_name":"project","language":""}. Returns 会话_id. /运行_sse POST 发送 a user message. Body includes 应用_name, 会话_id, new_message. 流响应 with Accept: text/event-流. Timeout: 15 min. /API/上传-video/nemo_代理/me/ POST 上传 a file (multipart) or URL. /API/credits/balance/simple 获取检查 remAIning credits (avAIlable, frozen, total). /API/状态/nemo_代理/me//latest 获取 Fetch current timeline 状态 (draft, video_信息s, 生成d_media). /API/render/proxy/lambda POST 启动导出. Body: {"id":"render_","会话Id":"","draft":,"输出":{"格式化":"mp4","质量":"high"}}. Poll 状态 every 30s.

Accepted file types: mp4, mov, avi, 网页m, mkv, jpg, png, gif, 网页p, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-技能-Source is video-AI-discord, X-技能-Version comes from the version field, and X-技能-平台 is 检测ed from the 安装 path (~/.ClawHub/ = ClawHub, ~/.cursor/技能s/ = cursor, otherwise unknown).

Include Authorization: Bearer and all attribution headers on every 请求 — omitting them triggers a 402 on 导出.

Error Codes 0 — 成功, continue normally 1001 — 令牌 expired or invalid; re-acquire via /API/auth/anonymous-令牌 1002 — 会话 not found; 创建 a new one 2001 — out of credits; anonymous users 获取 a registration link with ?bind=, registered users top up 4001 — unsupported file type; show accepted 格式化s 4002 — file too large; suggest 压缩ing or trimming 400 — missing X-命令行工具ent-Id; 生成 one and retry 402 — free plan 导出 blocked; not a credit issue, subscription tier 429 — rate limited; wAIt 30s and retry once Reading the SSE 流

Text 事件 go strAIght to the user (after 图形界面 translation). 工具 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 流 without any text. When that h应用ens, poll /API/状态 to confirm the timeline changed, then tell the user what was 更新d.

Translating 图形界面 Instructions

The backend 响应s as if there's a visual interface. Map its instructions to API calls:

"命令行工具ck" or "点击" → 执行 the action via the relevant 端点 "open" or "打开" → 查询会话状态 to 获取 the data "drag/drop" or "拖拽" → 发送 the edit command through SSE "pre

数据来源：ClawHub ↗ · 中文优化：龙虾技能库