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tk8544-b

Hydra Ai

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install hydra-ai
功能描述
Turn a 2-minute raw interview recording into 1080p multi-version edited clips just by typing what you need. Whether it's generating multiple edited video ver...
使用说明 (SKILL.md)

Getting Started

Send me your video clips and I'll handle the AI multi-stream editing. Or just describe what you're after.

Try saying:

  • "create a 2-minute raw interview recording into a 1080p MP4"
  • "split this video into multiple edited versions for different platforms"
  • "generating multiple edited video versions from a single source clip for content creators"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Hydra AI — Generate Multiple Videos From One

This tool takes your video clips and runs AI multi-stream editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute raw interview recording and want to split this video into multiple edited versions for different platforms — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips produce faster and more accurate multi-version outputs.

Matching Input to Actions

User prompts referencing hydra ai, 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: hydra-ai
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s 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.

Backend Response Translation

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

Backend says You 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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "split this video into multiple edited versions for different platforms" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "split this video into multiple edited versions for different platforms" → 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.

安全使用建议
This skill appears to be a normal client for the 'nemovideo' cloud rendering service. Before installing: (1) Confirm the service domain (mega-api-prod.nemovideo.ai) and review its privacy/retention policy because you will upload potentially sensitive video content. (2) Prefer supplying your own NEMO_TOKEN from a trusted account rather than relying on the skill's anonymous-token flow if you need auditing or control. (3) Ask the maintainer to clarify the config-path discrepancy (SKILL.md frontmatter vs registry) and what, if anything, the skill will read from ~/.config/nemovideo. (4) Understand that uploads and renders happen on the remote service and that attribution headers require reading the skill frontmatter and possibly the agent install path — if you are uncomfortable with any local path probing, request that the skill avoid that behavior. If those items are acceptable or clarified, the skill is coherent with its purpose.
功能分析
Type: OpenClaw Skill Name: hydra-ai Version: 1.0.0 The Hydra AI skill is a legitimate integration for a cloud-based video editing service (nemovideo.ai). It provides detailed instructions for the agent to manage sessions, handle file uploads, and process video editing tasks via a set of API endpoints. The logic includes standard security practices such as token management and instructions to avoid exposing sensitive API data to the user. No indicators of data exfiltration, malicious execution, or harmful prompt injection were found.
能力评估
Purpose & Capability
Name, description, and runtime actions (uploading video, creating sessions, starting renders) align with a cloud video-editing backend. The single required credential (NEMO_TOKEN) is appropriate for an API-backed service. Note: the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — this mismatch should be clarified.
Instruction Scope
Instructions stay within the stated purpose: they describe auth, session creation, SSE for edits, uploads, and render polling against mega-api-prod.nemovideo.ai. The skill asks the agent to derive attribution headers from the skill frontmatter and to detect install path for X-Skill-Platform (reading agent install path), which is reasonable but does expand file-system probing beyond purely API calls. It also includes logic to obtain an anonymous token if NEMO_TOKEN is not present (posts to the service to receive a token).
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is downloaded or written by an installer in the provided materials.
Credentials
Only NEMO_TOKEN is required (declared as primary credential), which matches the service usage. However, SKILL.md frontmatter also references a config path (~/.config/nemovideo/), which could imply reading local configuration files; the registry metadata did not list required config paths. Confirm whether the skill will read that config path and what data it expects (it may contain tokens or user config).
Persistence & Privilege
always is false and the skill is user-invocable; it does not request persistent or system-wide privileges and does not instruct modifications to other skills or global agent config. Autonomous invocation remains allowed (platform default).
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 hydra-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /hydra-ai 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
Hydra AI 1.0.0 initial release: - Instantly generate multiple edited 1080p video versions from a single upload using a conversational interface — no manual timeline work or export settings required. - Seamless onboarding with automatic authentication, session management, and transparent cloud backend handling. - Supports a wide range of file types and batching workflows; up to 500MB per file. - Clear, plain-language error messages and session guidance; robust handling of common issues (auth, credits, exports). - All requests use required attribution headers for reliable cloud processing and export. - Workflow examples, action routing, and pipeline details available for both new and advanced users.
元数据
Slug hydra-ai
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

Hydra Ai 是什么?

Turn a 2-minute raw interview recording into 1080p multi-version edited clips just by typing what you need. Whether it's generating multiple edited video ver... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 71 次。

如何安装 Hydra Ai?

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

Hydra Ai 是免费的吗?

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

Hydra Ai 支持哪些平台?

Hydra Ai 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 Hydra Ai?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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