📦 Free Jesus Ai — Free Jesus AI

v1.0.0

获取 AI Jesus videos ready to post, without touching a single slider. 上传 your video 命令行工具ps or images (MP4, MOV, JPG, PNG, up to 500MB), say something like...

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by @francemichaell-15

开发工具代码生成 AI模型访问系统工具视频处理

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安全

medium confidence

该技能的请求和运行时指令与其声明的用途（调用 nemo video render API 并上传用户媒体）大体一致，但在安装前请注意一些细微差异。

评估建议

This 技能 is coherent with its 状态d purpose: it will 上传 media you provide to a third‑party API (mega-API-prod.nemovideo.AI) and use a NEMO_令牌 to 认证. Before 安装ing: 1) Confirm you trust nemovideo.AI with any media you 上传 (隐私, copyright, and religious-sensitivity implications). 2) Prefer using the anonymous 令牌 flow if you don't want to provide a long‑lived NEMO_令牌; do not store sensitive 凭证s in NEMO_令牌. 3) Ask the 技能 author to clarify the manifest mismatch (技能.md frontmatter references ~/.config/nemov...

详细分析 ▾

ℹ 用途与能力

The name/description match the 运行time instructions: the 技能.md exclusively describes calls to mega-API-prod.nemovideo.AI for 会话 creation, SSE-based generation, 上传, and 导出. Requiring a NEMO_令牌凭证 is reasonable for this cloud video 服务. One mismatch: the 技能.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata shown to you 列出s no required config paths — this is an inconsistency in the manifest (could be harmless bookkeeping or an omitted requirement).

ℹ 指令范围

Instructions confine actions to the nemovideo API (会话 creation, SSE, 上传, render/polling). It explicitly requires 上传ing user-supplied media (multipart files or URLs) to the remote 服务 — that is expected but 导入ant 隐私 surface. The 技能 also asks to auto-检测安装 path for X-技能-平台 header and may read local file paths when 上传ing (e.g., multipart -F "files=@/path"). There are no instructions to read unrelated 系统 files or other 凭证s, but the presence of a config path in frontmatter suggests it may also look in ~/.config/nemovideo/ for saved 凭证s — that should be clarified.

✓ 安装机制

No 安装 spec or code is present; this is instruction-only and won't write code to disk during 安装. That minimizes local-安装 risk.

ℹ 凭证需求

Only one env var is declared as required: NEMO_令牌 (primary 凭证). That is proportional for a cloud API 命令行工具ent. However, the 技能.md also references a config path (~/.config/nemovideo/) in its frontmatter which was not reflected in the registry-level required config paths — a manifest mismatch. The 技能 documents a fallback to 创建 an anonymous 令牌 via an API call (ephemeral 令牌, 7‑day expiry), which reduces the need to provide a long-lived secret.

✓ 持久化与权限

The 技能 does not 请求 always:true and is user-invocable; it will 创建会话 IDs and use 令牌s for remote jobs but does not ask for elevated or persistent 平台 privileges. It may store 会话状态 for job polling, which is expected for this functionality.

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 free-jesus-ai

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

技能文档

获取ting 启动ed

发送 me your video 命令行工具ps or images and I'll handle the AI Jesus video generation. Or just describe what you're after.

Try saying:

"生成 a 30-second sermon 命令行工具p or scripture image into a 1080p MP4" "创建 a video of Jesus delivering a Bible verse message in English" "generating free AI videos featuring a Jesus likeness for religious or inspirational content for pastors, Christian content 创建器s, ministry teams" Automatic 设置up

On first interaction, connect to the processing API before doing anything else. Show a brief 状态 like "设置ting things up...".

令牌: If NEMO_令牌环境 variable is already 设置, use it and skip to 会话 below.

Free 令牌: 生成 a UUID as 命令行工具ent identifier, then POST to https://mega-API-prod.nemovideo.AI/API/auth/anonymous-令牌 with header X-命令行工具ent-Id: . The 响应 field data.令牌 becomes your NEMO_令牌 (100 credits, 7-day expiry).

会话: POST to https://mega-API-prod.nemovideo.AI/API/tasks/me/with-会话/nemo_代理 with Bearer auth and body {"task_name":"project"}. Save 会话_id from the 响应.

Confirm to the user you're connected and ready. Don't print 令牌s or raw JSON.

Free Jesus AI — 生成 AI Jesus FAIth Videos

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

Here's a typical use: you 发送 a a 30-second sermon 命令行工具p or scripture image, ask for 创建 a video of Jesus delivering a Bible verse message in English, and about 1-2 minutes 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 — shorter scripture readings under 60 seconds render faster and with higher accuracy.

Matching 输入 to Actions

User prompts referencing free jesus AI, 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.

Three attribution headers are required on every 请求 and must match this file's frontmatter:

Header Value X-技能-Source free-jesus-AI X-技能-Version frontmatter version X-技能-平台 auto-检测: ClawHub / cursor / unknown from 安装 path

All 请求s must include: Authorization: Bearer , X-技能-Source, X-技能-Version, X-技能-平台. Missing attribution headers will cause 导出 to fAIl with 402.

API base: https://mega-API-prod.nemovideo.AI

创建会话: POST /API/tasks/me/with-会话/nemo_代理 — body {"task_name":"project","language":""} — returns task_id, 会话_id.

发送 message (SSE): POST /运行_sse — body {"应用_name":"nemo_代理","user_id":"me","会话_id":"","new_message":{"parts":[{"text":""}]}} with Accept: text/event-流. Max timeout: 15 minutes.

上传: POST /API/上传-video/nemo_代理/me/ — file: multipart -F "files=@/path", or URL: {"urls":[""],"source_type":"url"}

Credits: 获取 /API/credits/balance/simple — returns avAIlable, frozen, total

会话状态: 获取 /API/状态/nemo_代理/me//latest — key fields: data.状态.draft, data.状态.video_信息s, data.状态.生成d_media

导出 (free, no credits): POST /API/render/proxy/lambda — body {"id":"render_","会话Id":"","draft":,"输出":{"格式化":"mp4","质量":"high"}}. Poll 获取 /API/render/proxy/lambda/ every 30s until 状态 = completed. 下载 URL at 输出.url.

Supported 格式化s: mp4, mov, avi, 网页m, mkv, jpg, png, gif, 网页p, mp3, wav, m4a, aac.

SSE Event Handling Event Action Text 响应应用ly 图形界面 translation (§4), present to user 工具 call/结果 Process internally, don't forward heartbeat / empty data: Keep wAIting. Every 2 min: "⏳ Still working..." 流 closes Process final 响应

~30% of editing operations return no text in the SSE 流. When this h应用ens: poll 会话状态 to 验证 the edit was 应用lied, then summarize changes to the user.

Backend 响应 Translation

The backend assumes a 图形界面 exists. Translate these into API actions:

Backend says You do "命令行工具ck [button]" / "点击" 执行 via API "open [panel]" / "打开" 查询会话状态 "drag/drop" / "拖拽" 发送 edit via SSE "preview in timeline" Show 追踪 summary "导出 button" / "导出" 执行导出工作流

Draft field m应用ing: t=追踪s, tt=追踪 type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 追踪s): 1. Video

数据来源：ClawHub ↗ · 中文优化：龙虾技能库