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vynbosserman65

Image To Video Honor

by vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-honor
Description
Get animated tribute video ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like...
README (SKILL.md)

Getting Started

Share your still images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "turn this photo into a tribute"

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.

Image to Video Honor — Create Tribute Videos from Photos

This tool takes your still images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a portrait photo or award ceremony image and want to turn this photo into a tribute video with motion effects and music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-resolution images produce smoother motion and sharper final output.

Matching Input to Actions

User prompts referencing image to video honor, 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-honor, 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).

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.

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

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool 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 stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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)

Common Workflows

Quick edit: Upload → "turn this photo into a tribute video with motion effects and music" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this photo into a tribute video with motion effects and music" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across social and presentation platforms.

Usage Guidance
This skill will upload your images to an external service (mega-api-prod.nemovideo.ai) to render videos. Before installing: (1) Consider privacy — do not upload sensitive images unless you trust the service and its retention policy. (2) The skill can create an anonymous token automatically if NEMO_TOKEN is not set; decide whether you prefer to supply and manage your own token. (3) The skill may probe common install paths and read local upload file paths to operate; ensure you are comfortable granting that file access. (4) There is no source/homepage listed — verify the upstream service (nemovideo) and its terms/privacy independently before use. If you proceed, prefer creating an explicit account/token via the vendor site (rather than relying on anonymous tokens), and monitor what files are uploaded.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-honor Version: 1.0.0 The skill is a legitimate integration for an image-to-video conversion service hosted at mega-api-prod.nemovideo.ai. It provides clear instructions for the AI agent to manage authentication tokens, sessions, and file uploads required for its stated purpose. No evidence of data exfiltration, malicious code execution, or harmful prompt injection was found.
Capability Assessment
Purpose & Capability
Name/description align with the actions described in SKILL.md: uploading images, creating jobs, polling renders, and returning MP4s. The single required credential (NEMO_TOKEN) is consistent with a cloud rendering backend.
Instruction Scope
Instructions include all API calls expected for a cloud render pipeline (auth, session create, SSE, upload, export). Concerns: (1) If NEMO_TOKEN is missing the skill automatically requests an anonymous token on the user's behalf — this creates credentials without an explicit user action. (2) The doc says it will detect the install path (e.g., ~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform, which implies probing host filesystem locations that were not declared in metadata. (3) The skill also references multipart uploads from local file paths ("@/path") — the agent will need access to whatever local temp path receives user uploads. These file/path actions expand the scope beyond pure network calls and should be considered by the user.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. This is low install risk.
Credentials
Only NEMO_TOKEN is required (declared as primaryEnv), which fits the backend integration. However the skill also documents a flow to obtain an anonymous NEMO_TOKEN automatically, meaning the declared env var is optional in practice. Metadata lists a configPath (~/.config/nemovideo/) that could hold tokens/config — if the agent reads/writes that path it should be disclosed to the user.
Persistence & Privilege
always is false and the skill does not request system-wide persistence. The main privilege concern is network upload of user images to an external API and the skill's implied ability to read certain local paths to detect platform or read upload files; these are expected for this use-case but should be explicit and consented to.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-honor
  3. After installation, invoke the skill by name or use /image-to-video-honor
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Image to Video Honor. - Instantly create tribute videos from uploaded images with AI-powered motion effects and music. - Simple, no-edit UI: upload, give instructions, and receive a 1080p MP4 ready to share. - Supports JPG, PNG, WEBP, HEIC images up to 200MB; exports in multiple formats. - Automatically manages cloud session setup and free token generation. - Built-in workflows for uploading, editing, exporting, and credit management. - Designed for speed and ease of use—no video editing experience required.
Metadata
Slug image-to-video-honor
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image To Video Honor?

Get animated tribute video ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like... It is an AI Agent Skill for Claude Code / OpenClaw, with 96 downloads so far.

How do I install Image To Video Honor?

Run "/install image-to-video-honor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Image To Video Honor free?

Yes, Image To Video Honor is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Image To Video Honor support?

Image To Video Honor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Image To Video Honor?

It is built and maintained by vynbosserman65 (@vynbosserman65); the current version is v1.0.0.

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