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vcarolxhberger

Caption Maker

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install caption-maker
功能描述
Skip the learning curve of professional editing software. Describe what you want — add captions in English and Spanish with auto-sync — and get captioned vid...
使用说明 (SKILL.md)

Getting Started

Share your video files and I'll get started on AI subtitle generation. Or just tell me what you're thinking.

Try saying:

  • "add my video files"
  • "export 1080p MP4"
  • "add captions in English and Spanish"

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 \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. 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.

Caption Maker — Add Captions to Any Video

Drop your video files in the chat and tell me what you need. I'll handle the AI subtitle generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute YouTube tutorial recording, ask for add captions in English and Spanish with auto-sync, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 2 minutes process significantly faster.

Matching Input to Actions

User prompts referencing caption maker, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is caption-maker, 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).

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

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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.

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 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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add captions in English and Spanish with auto-sync" — 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 all platforms.

Common Workflows

Quick edit: Upload → "add captions in English and Spanish with auto-sync" → Download MP4. Takes 30-60 seconds 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 will upload your videos and metadata to a third-party service (mega-api-prod.nemovideo.ai) and may automatically obtain a short-lived anonymous token if you don't supply one. Before installing: (1) confirm you are comfortable sending your videos to that external domain (avoid uploading sensitive/private video). (2) Consider providing your own NEMO_TOKEN if you want control over credentials instead of letting the skill fetch one. (3) Ask the provider about data retention and deletion policies (how long uploaded media and generated captions are kept). (4) Be aware the skill sends a header that may reveal where the skill is installed (it inspects common install paths) — if that matters, ask for that behavior to be removed. (5) If you need higher assurance, verify the service domain and operator independently (no homepage or publisher info was provided).
功能分析
Type: OpenClaw Skill Name: caption-maker Version: 1.0.0 The caption-maker skill is a functional integration for a video processing service hosted at nemovideo.ai. It manages video uploads, AI caption generation, and rendering via a cloud API. The skill's behavior, including environment variable access (NEMO_TOKEN), local configuration storage (~/.config/nemovideo/), and automated session management, is consistent with its stated purpose. There are no indicators of data exfiltration, unauthorized command execution, or malicious prompt injection.
能力评估
Purpose & Capability
The declared purpose (cloud captioning) matches the runtime actions (upload files, request renders, download results). Requesting a NEMO_TOKEN is expected. However, the metadata declares NEMO_TOKEN as required while the SKILL.md also instructs the agent to automatically obtain an anonymous token if none is set — this redundancy is inconsistent. The metadata also lists a config path (~/.config/nemovideo/) that the instructions never explicitly read, which is unnecessary or at least unexplained.
Instruction Scope
Instructions direct the agent to POST files and messages to an external domain (mega-api-prod.nemovideo.ai), obtain/store session tokens, and include headers that reveal detected install paths. Reading/detecting install locations (~/.clawhub/, ~/.cursor/skills/) and adding them to request headers leaks local environment details that are unrelated to captioning quality. The skill will auto-generate and store tokens and session IDs for subsequent requests — this is expected for a cloud service but is a privacy surface worth noting.
Install Mechanism
No install spec and no code files — instruction-only. That is the lowest-risk install mechanism: nothing additional is written to disk by an installer step. The behavioral risk comes from the runtime network calls described in SKILL.md, not from an installer.
Credentials
Only one credential (NEMO_TOKEN) is declared, which is proportionate for a cloud API. But the SKILL.md's automatic anonymous-token flow (POST to anonymous-token) means the skill can obtain credentials without you providing them. The declared configPaths value is not justified by the instructions. Overall the credential request is explainable, but the automatic acquisition and local-path detection reduce transparency.
Persistence & Privilege
The skill is not force-enabled (always: false) and uses normal autonomous invocation. It does instruct storing session_id and tokens for subsequent requests, which is normal for a session-based API; there is no claim it modifies other skills or system-wide config.
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 caption-maker
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /caption-maker 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
- Initial release of Caption Maker — add captions to video files with AI auto-sync. - Supports English and Spanish captions on MP4, MOV, AVI, and WebM files up to 500MB. - Simple, guided setup with instant authentication and seamless cloud processing (no local installation needed). - Process videos in 30–60 seconds and export captioned files in up to 1080p. - Easy commands for uploading, getting export links, and checking credits. - Designed for creators who want fast, accurate captions without manual editing.
元数据
Slug caption-maker
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

Caption Maker 是什么?

Skip the learning curve of professional editing software. Describe what you want — add captions in English and Spanish with auto-sync — and get captioned vid... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 45 次。

如何安装 Caption Maker?

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

Caption Maker 是免费的吗?

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

Caption Maker 支持哪些平台?

Caption Maker 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 Caption Maker?

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

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