AgentKit Shopping Avatar Video
anbeime/skill
Chinese-language skill that produces a 25-second vertical video of a digital shopping-guide avatar for e-commerce, chaining AI image, voice and video generation.
The ai-image-to-video-generator skill on ClawHub transforms static images into dynamic, motion-rich video content through a conversational interface.
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generator --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-image-to-video-generator .claude/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .claude/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generatorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generator --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-image-to-video-generator .agents/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .agents/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generator --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-image-to-video-generator .cursor/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .cursor/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/ai-image-to-video-generator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generator --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-image-to-video-generator .gemini/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .gemini/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generatorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-image-to-video-generator .github/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .github/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills ai-image-to-video-generator --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-image-to-video-generator .opencode/skills/ai-image-to-video-generator && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-image-to-video-generator" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/ai-image-to-video-generator into .opencode/skills/ai-image-to-video-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-to-video-generator", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ai-image-to-video-generatorThe ai-image-to-video-generator skill on ClawHub transforms static images into dynamic, motion-rich video content through a conversational interface.
AI Image To Video Generator is an agent skill from LeoYeAI/openclaw-master-skills. The ai-image-to-video-generator skill on ClawHub transforms static images into dynamic, motion-rich video content through a conversational interface. Upload any photo or illustration, describe the motion style you want, and receive a polished video output. Ideal for marketers, content creators, and social media managers who need animated visuals without complex software. Supports mp4, mov, avi, webm, and mkv output formats.
Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `_meta.json`).
It sits in Media & Creative, covering AI video generation, Image generation and Blog and article writing. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
mega-api-prod.nemovideo.ainemovideo.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
NEMO_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AI Image To Video Generator loads about 4.1k tokens when it runs. Until then it costs about 114 tokens; SKILL.md has 1,764 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,764 words, ~4,090 tokens.
.claude/skills/ai-image-to-video-generator/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.When the user opens this skill or sends their first message, greet them immediately:
📱 Ready to image to video generator! Just send me a video or describe your project.
Try saying:
IMPORTANT: Do NOT wait silently. Always greet the user proactively on first contact.
Before responding to the user, complete these steps invisibly:
NEMO_TOKEN env var is set, use it. Otherwise:~/.config/nemovideo/client_id if it exists~/.config/nemovideo/client_idcurl -s -X POST "$API/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"token as NEMO_TOKEN for this session. You get 100 free credits.CRITICAL: Never mention tokens, authentication, API setup, or Client-IDs to the user. The user should feel like the skill "just works".
Still images carry meaning, but video captures attention. This skill bridges that gap by letting you describe exactly how you want your image to move — whether that's a gentle parallax drift, a dramatic zoom, flowing particle effects, or scene transitions — and delivering a rendered video that matches your creative intent.
The experience is fully conversational. Rather than wrestling with timelines, keyframes, or motion curves, you simply describe what you want in plain language. The OpenClaw agent interprets your instructions, communicates with the underlying AI video synthesis backend, and iterates with you until the result feels right. You can refine motion speed, direction, loop behavior, and visual tone across multiple turns in the same session.
Under the hood, the AI backend analyzes depth, subject boundaries, and visual composition within your source image to generate plausible, coherent motion that respects the original scene. The result is not a slideshow or a pan-and-scan effect — it is a genuinely animated video derived from a single frame. Final exports are available in mp4, mov, avi, webm, and mkv formats to fit any platform or publishing workflow.
| Variable | Required | Default |
|---|---|---|
NEMO_TOKEN | No | Auto-generated (100 free credits, expires in 7 days, revocable via Settings → API Tokens) |
NEMO_API_URL | No | https://mega-api-prod.nemovideo.ai |
NEMO_WEB_URL | No | https://nemovideo.com |
NEMO_CLIENT_ID | No | Auto-generated UUID, persisted to ~/.config/nemovideo/client_id (UUID only, no secrets) |
SKILL_SOURCE | No | Auto-detected from install path, fallback unknown |
If NEMO_TOKEN is not set, get one (requires X-Client-Id header):
# Generate or read persisted Client-Id
CLIENT_ID="${NEMO_CLIENT_ID:-$(cat ~/.config/nemovideo/client_id 2>/dev/null)}"
if [ -z "$CLIENT_ID" ]; then
CLIENT_ID=$(uuidgen 2>/dev/null || echo "client-$(date +%s)-$RANDOM")
mkdir -p ~/.config/nemovideo && echo "$CLIENT_ID" > ~/.config/nemovideo/client_id
fi
curl -s -X POST "$API/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"
# → {"code":0,"data":{"token":"nmv_usr_xxx","credits":100,...}}Save token as NEMO_TOKEN, CLIENT_ID as NEMO_CLIENT_ID. Anonymous: 1 token per client per 7 days; token expires in 7 days and can be revoked at any time via Settings → API Tokens on nemovideo.com. If your token expires, request a new one with the same X-Client-Id.
Local persistence: This skill writes ~/.config/nemovideo/client_id to persist the Client-Id across sessions. This avoids generating a new ID on every request, which would hit the per-IP rate limit quickly (default 10 tokens per 7 days per IP). The file contains only a UUID — no credentials are stored locally.
Use the following table to determine which endpoint handles each type of incoming request.
| 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 | ❌ |
$API = ${NEMO_API_URL:-https://mega-api-prod.nemovideo.ai}, $TOKEN = ${NEMO_TOKEN}, $WEB = ${NEMO_WEB_URL:-https://nemovideo.com}.
Skill attribution variables — do NOT hardcode:
$SKILL_NAME = this file's YAML frontmatter name$SKILL_VERSION = this file's YAML frontmatter version$SKILL_SOURCE = detect at runtime using the first match:SKILL_SOURCE if set~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor)unknownCRITICAL: ALL API requests (including render/export/upload/state/credits) MUST include these headers. Missing them will cause export to fail with 402.
X-Skill-Source: $SKILL_NAME
X-Skill-Version: $SKILL_VERSION
X-Skill-Platform: $SKILL_SOURCEcurl -s -X POST "$API/api/tasks/me/with-session/nemo_agent" \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" \
-d '{"task_name":"project","language":"<lang>"}'
# → {"code":0,"data":{"task_id":"...","session_id":"..."}}A session must be initialized before any other operations can proceed. This creates the context that all subsequent requests will be tied to.
Open in browser: After creating a session, give the user a link to view/edit the task in NemoVideo:
$WEB/workspace/claim?token=$TOKEN&task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE
curl -s -X POST "$API/run_sse" \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-H "Accept: text/event-stream" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" --max-time 900 \
-d '{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}'All conversational messages are transmitted to the backend through a Server-Sent Events connection.
| Event | Action |
|---|---|
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Wait silently, don't forward |
heartbeat / empty data: | Keep waiting. Every 2 min: "⏳ Still working..." |
| Stream closes | Process final response |
Typical durations: text 5-15s, video generation 100-300s, editing 10-30s.
Timeout: 10 min heartbeats-only → assume timeout. Never re-send during generation (duplicates + double-charge).
Ignore trailing "I encountered a temporary issue" if prior responses were normal.
Approximately 30% of edit operations return no visible text in the response. When this occurs: (1) do not treat the absence of text as a failure, (2) poll the task state endpoint to confirm processing is underway, (3) once the task reaches a completed state, proceed directly to the export step, and (4) inform the user that their edit is being processed without alarming them about the lack of a text reply.
Two-stage generation: After the raw video is produced, the backend automatically initiates a second processing stage that layers in background music and a title sequence. Do not treat the first completed video as the final deliverable — wait for both stages to finish before presenting the result to the user.
File upload: curl -s -X POST "$API/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -F "files=@/path/to/file"
URL upload: curl -s -X POST "$API/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -d '{"urls":["<url>"],"source_type":"url"}'
Use me in the path; backend resolves user from token.
Supported: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
The upload endpoint accepts image and video files that will serve as source material for generation tasks.
curl -s "$API/api/credits/balance/simple" -H "Authorization: Bearer $TOKEN" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"
# → {"code":0,"data":{"available":XXX,"frozen":XX,"total":XXX}}Query the credits endpoint before initiating any generation task to confirm the user has a sufficient balance.
curl -s "$API/api/state/nemo_agent/me/<sid>/latest" -H "Authorization: Bearer $TOKEN" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"Use me for user in path; backend resolves from token.
Key fields: data.state.draft, data.state.video_infos, data.state.canvas_config, data.state.generated_media.
Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.
Draft ready for export when draft.t exists with at least one track with non-empty sg.
Track summary format:
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)Export does NOT cost credits. Only generation/editing consumes credits.
Triggering an export does not deduct any credits from the user's balance. To deliver the finished asset: (a) call the export endpoint once the task is confirmed complete, (b) retrieve the download URL from the response, (c) verify the URL is accessible, (d) present the link or embed the asset directly in the chat, and (e) confirm successful delivery to the user.
b) Submit: curl -s -X POST "$API/api/render/proxy/lambda" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -d '{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}'
Note: sessionId is camelCase (exception). On failure → new id, retry once.
c) Poll (every 30s, max 10 polls): curl -s "$API/api/render/proxy/lambda/<id>" -H "Authorization: Bearer $TOKEN" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"
Status at top-level status: pending → processing → completed / failed. Download URL at output.url.
d) Download from output.url → send to user. Fallback: $API/api/render/proxy/<id>/download.
e) When delivering the video, always also give the task detail link: $WEB/workspace/claim?token=$TOKEN&task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE
Progress messages: start "⏳ Rendering ~30s" → "⏳ 50%" → "✅ Video ready!" + file + task detail link.
If the SSE stream drops unexpectedly, follow these steps to recover: (1) detect the disconnection event and log it internally without surfacing an error to the user prematurely, (2) attempt to re-establish the SSE connection using the existing session ID, (3) if reconnection succeeds, resume listening for task progress events from where the stream left off, (4) if reconnection fails after the maximum number of retries, fall back to polling the task state endpoint at a regular interval, and (5) once a terminal task state is confirmed, proceed with the export flow as normal.
The backend operates under the assumption that a graphical interface is present, so GUI-specific instructions must never be passed through directly to the user.
| Backend says | You do |
|---|---|
| "click [button]" / "点击" | Execute via API |
| "open [panel]" / "打开" | Show state via §3.4 |
| "drag/drop" / "拖拽" | Send edit via SSE |
| "preview in timeline" | Show track summary |
| "Export button" / "导出" | Execute §3.5 |
| "check account/billing" | Check §3.3 |
Keep content descriptions. Strip GUI actions.
• Acknowledge the user's request immediately and set clear expectations about processing time before the generation task begins. • Provide incremental progress updates during long-running tasks so users remain informed without needing to ask. • When a task completes, always surface the final exported asset rather than an intermediate result. • If the user submits an ambiguous prompt, ask a single focused clarifying question rather than making assumptions. • After delivering the finished video, invite the user to request edits or refinements to keep the conversation moving forward.
• Generation tasks can take several minutes to complete; real-time delivery is not possible. • The system does not support more than one concurrent generation task per session. • Source images must meet minimum resolution requirements or the upload will be rejected. • Background music and title overlays are applied automatically and cannot be individually disabled through the API. • Credit balances are read-only via the API; top-ups must be handled through the platform's billing interface.
The table below maps common error codes to their likely causes and the recommended recovery action for each.
| 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=<id> (get <id> from create-session or state response when needed). Registered: "Top up at nemovideo.ai" |
| 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 at nemovideo.ai to unlock export." |
| 429 | Rate limit (1 token/client/7 days) | Retry in 30s once |
Common: no video → generate first; render fail → retry new id; SSE timeout → §3.6; silent edit → §3.1 fallback.
Always verify that the API version header matches the version documented in this skill before making requests, as older versions may not support all endpoints described here. The access token provided at session creation must include the required scopes for generation, upload, export, and credits reading; requests made with tokens missing any of these scopes will return a 403 response.
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/ai-image-to-video-generator of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
AI Image To Video Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Image To Video Generator this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.1k | Automated safety check: Pass | MIT | |
| AgentKit Shopping Avatar Videoanbeime/skill | 7.8k | — | ~1k | Automated safety check: Pass | None | |
| Commercial Media Productionfal-ai-community/skills | 251 | — | ~1.5k | Automated safety check: Pass | None | |
| Genmedia Media Workflowsfal-ai-community/skills | 251 | — | ~1.3k | Automated safety check: Pass | None | |
| SN Motion HTMLOpenSenseNova/SenseNova-Skills | 5.7k | — | ~2.2k | Automated safety check: Notes | MIT | |
| Seedance Storyboard Generatorliangdabiao/Seedance2-Storyboard-Generator | 2.6k | — | ~2.2k | Automated safety check: Pass | None |
anbeime/skill
Chinese-language skill that produces a 25-second vertical video of a digital shopping-guide avatar for e-commerce, chaining AI image, voice and video generation.
fal-ai-community/skills
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fal-ai-community/skills
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OpenSenseNova/SenseNova-Skills
Builds HTML stories where one continuous camera journey advances with page progress, using researched structure, AI stills, Seedance video clips and browser QA.
liangdabiao/Seedance2-Storyboard-Generator
专业的Seedance 2.0平台AI视频脚本和分镜生成器。当用户要求:(1) 将文章/故事转换为视频脚本,(2) 生成Seedance 2.0分镜提示词,(3) 规划多集AI视频系列,(4) 为GPT-Image-2、Seedream、Nano Banana…
nexu-io/nexu
Seedance 2.0 video & image generation via LibTV Gateway - AI text-to-video, image-to-video, video continuation, style transfer, and text-to-image using Seedance 2.0 model.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Categories
The ai-image-to-video-generator skill on ClawHub transforms static images into dynamic, motion-rich video content through a conversational interface. AI Image To Video Generator is an agent skill from LeoYeAI/openclaw-master-skills. The ai-image-to-video-generator skill on ClawHub transforms static images into dynamic, motion-rich video content through a conversational interface.
AI Image To Video Generator fits situations like: tasks that involve AI video generation; tasks that involve Image generation; tasks that involve Blog and article writing.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a claude-code`. Or copy the skill folder (skills/ai-image-to-video-generator in LeoYeAI/openclaw-master-skills) into .claude/skills/ai-image-to-video-generator in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a codex`. Or copy the skill folder (skills/ai-image-to-video-generator in LeoYeAI/openclaw-master-skills) into .agents/skills/ai-image-to-video-generator in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill ai-image-to-video-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-image-to-video-generator, .gemini/skills/ai-image-to-video-generator, .github/skills/ai-image-to-video-generator and .opencode/skills/ai-image-to-video-generator in your project.
Going by SKILL.md and its folder, AI Image To Video Generator needs the command-line tools its instructions call (curl) and credentials named NEMO_TOKEN. Our summary lists: A credential in NEMO_TOKEN.
SKILL.md names 2 domains. In commands or code: mega-api-prod.nemovideo.ai and nemovideo.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AI Image To Video Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AI Image To Video Generator: AgentKit Shopping Avatar Video (anbeime/skill, 7.8k stars), Commercial Media Production (fal-ai-community/skills, 251 stars), Genmedia Media Workflows (fal-ai-community/skills, 251 stars) and SN Motion HTML (OpenSenseNova/SenseNova-Skills, 5.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.