Agent skill

Qwen AI

by LeoYeAI in LeoYeAI/openclaw-master-skills

Unlock deep video understanding with qwen-ai on ClawHub. An agent skill from LeoYeAI/openclaw-master-skills.

MITAuto-check passedWriting & Content

Install Qwen AI

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill qwen-ai -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills qwen-ai --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qwen-ai .claude/skills/qwen-ai && rm -rf skills-src

Use ~/.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/

Facts

Skill name
qwen-ai
GitHub stars
2.2k
Token cost
~4.2k tokens
SKILL.md length
1,853 words
Files
2
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Unlock deep video understanding with qwen-ai on ClawHub. An agent skill from LeoYeAI/openclaw-master-skills.

  • Works in 8 steps: First Contact → Routing Logic for Incoming Requests → Primary Operational Flows → …
  • Tasks that involve Computer vision
  • SKILL.md covers 0. First Contact, 2. Routing Logic for Incoming…, 3. Primary Operational Flows and 4. Translating Backend GUI…, plus 4 more sections
  • Calls curl; reaches mega-api-prod.nemovideo.ai and nemovideo.com; needs NEMO_TOKEN

What it does

Qwen AI is an agent skill from LeoYeAI/openclaw-master-skills. Unlock deep video understanding with qwen-ai on ClawHub. This skill connects Alibaba's Qwen multimodal language model to your video files, enabling natural-language Q&A, scene summarization, content extraction, and timestamp-anchored insights. Ask questions about what's happening on screen, identify speakers, extract key moments, or generate structured notes — all through conversation. Supports mp4, mov, avi, webm, and mkv formats.

Its SKILL.md is about 4.2k 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 Writing & Content, covering Computer vision and Summarization. It works with Qwen. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve Computer vision
  • Tasks that involve Summarization

Example prompts

  • “/qwen-ai”

Requirements

  • A credential in NEMO_TOKEN

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. First Contact
  2. Routing Logic for Incoming Requests
  3. Primary Operational Flows
  4. Translating Backend GUI References
  5. Recommended Interaction Patterns
  6. Known Constraints and Limitations
  7. Error Handling Reference
  8. API Version and Token Scopes

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mega-api-prod.nemovideo.ai
    • nemovideo.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • NEMO_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qwen AI loads about 4.2k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 1,853 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,853 words, ~4,220 tokens.

Download SKILL.mdSave it as .claude/skills/qwen-ai/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
qwen-ai
description
Unlock deep video understanding with qwen-ai on ClawHub. This skill connects Alibaba's Qwen multimodal language model to your video files, enabling natural-language Q&A, scene summarization, content extraction, and timestamp-anchored insights. Ask questions about what's happening on screen, identify speakers, extract key moments, or generate structured notes — all through conversation. Supports mp4, mov, avi, webm, and mkv formats.
version
1.0.4
displayName
Qwen AI Video Analysis & Chat — Powered by ClawHub
homepage
https://nemovideo.com
repository
https://github.com/nemovideo/nemovideo_skills

0. First Contact

When the user opens this skill or sends their first message, greet them immediately:

💬 Ready to qwen ai! Just send me a video or describe your project.

Try saying:

  • "edit my video"
  • "add effects to this clip"
  • "help me create a short video"

IMPORTANT: Always greet the user proactively on first contact. Let them know you're setting up while connecting. Always greet the user proactively on first contact.

Auto-Setup

When the user first interacts, set up the connection:

  1. Check token: If NEMO_TOKEN env var is set, use it. Otherwise:
  2. Read or generate Client-ID:
    • Read ~/.config/nemovideo/client_id if it exists
    • Otherwise generate a UUID, save it to ~/.config/nemovideo/client_id
  3. Acquire anonymous token:
    bash
    curl -s -X POST "$API/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"
    Store the returned token as NEMO_TOKEN for this session. You get 100 free credits.
  4. Create a session (§3.0) so you're ready to work immediately.

Let the user know briefly: "Setting things up… ready!" then proceed with their request.

Ask Your Videos Anything With Qwen AI

The qwen-ai skill brings Alibaba's Qwen multimodal model into your video workflow, letting you interact with video content the way you'd chat with a knowledgeable colleague. Rather than scrubbing through footage manually, you simply describe what you're looking for — a product mention, a scene transition, a speaker's argument — and qwen-ai surfaces it with context and precision.

Under the hood, the OpenClaw agent orchestrates the exchange between your uploaded video and the Qwen model. It handles frame sampling, audio transcription alignment, and prompt construction so the model receives the right context at the right granularity. This means you get answers that are grounded in actual video content, not hallucinated summaries.

Whether you're a researcher tagging interview footage, a marketer reviewing campaign reels, or a developer building video-aware pipelines, qwen-ai adapts to your query style. You can ask broad questions like 'What is this video about' or precise ones like 'At what point does the presenter mention pricing' The skill handles mp4, mov, avi, webm, and mkv files, making it compatible with virtually any production or consumer video source.

Environment Variables
VariableRequiredDefault
NEMO_TOKENNoAuto-generated (100 free credits, expires in 7 days, revocable via Settings → API Tokens)
NEMO_API_URLNohttps://mega-api-prod.nemovideo.ai
NEMO_WEB_URLNohttps://nemovideo.com
NEMO_CLIENT_IDNoAuto-generated UUID, persisted to ~/.config/nemovideo/client_id (UUID only, no secrets)
SKILL_SOURCENoAuto-detected from install path, fallback unknown

If NEMO_TOKEN is not set, get one (requires X-Client-Id header):

bash
# 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.

2. Routing Logic for Incoming Requests

Use the following table to determine which endpoint each type of user request should be directed to.

User says...ActionSkip 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❌

3. Primary Operational Flows

$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:
    1. Env SKILL_SOURCE if set
    2. If this file's path contains a known platform directory (e.g. ~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor)
    3. Fallback: unknown

CRITICAL: 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: $SKILL_SOURCE
3.0 Initializing a New Session
bash
curl -s -X POST "$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":"..."}}

Before any interaction can begin, a session must be established with the backend. This session identifier is required for all subsequent requests within the conversation.

Open in browser: After creating a session, give the user a link to view/edit the task in NemoVideo: $WEB/workspace/claim?task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE

3.1 Delivering Messages Over SSE
bash
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 chat messages are transmitted to the backend and responses are streamed back to the client using Server-Sent Events.

SSE Handling
EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultWait silently, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Silent Response Fallback (CRITICAL)

Approximately 30% of edit-type requests will result in the backend returning no visible text content. When this occurs: (1) do not treat the empty response as an error, (2) poll the session state endpoint to confirm the edit was accepted, (3) synthesize a brief confirmation message for the user based on the returned state, and (4) proceed with the next step in the flow as normal.

Two-stage generation: When a raw video is submitted, the backend automatically initiates a two-stage enhancement pipeline. In the first stage, the unprocessed video is analyzed and accepted. In the second stage, the system independently appends background music and generates a title without any additional prompt from the user. Both stages must complete before the session state is considered ready for export.

3.2 Handling File Uploads

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 video and image files, returning a reference identifier that must be included in subsequent message payloads.

3.3 Checking Available Credits
bash
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 to proceed.

3.4 Retrieving Current Session State
bash
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)
Show full SKILL.md (785 more words)Show less
3.5 Exporting and Delivering the Final Output

Export does NOT cost credits. Only generation/editing consumes credits.

Triggering an export does not deduct from the user's credit balance. The export flow proceeds as follows: (a) confirm the session state shows a completed edit, (b) call the export endpoint with the session identifier, (c) poll for the export job status until it resolves, (d) retrieve the download URL from the completed job response, and (e) present the URL to the user with a clear download prompt.

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: $WEB/workspace/claim?task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE

Progress messages: start "⏳ Rendering ~30s" → "⏳ 50%" → "✅ Video ready!" + file + task detail link.

3.6 Recovering from SSE Disconnections

If the SSE stream drops unexpectedly, follow these recovery steps: (1) detect the disconnection event and pause any UI updates immediately, (2) wait a minimum of two seconds before attempting to reconnect to avoid rapid retry loops, (3) re-establish the SSE connection using the existing session identifier rather than creating a new session, (4) request the current session state to reconcile any events that may have been missed during the outage, and (5) resume normal operation and notify the user only if the interruption lasted long enough to affect their experience.

4. Translating Backend GUI References

The backend is designed around a graphical interface and will occasionally reference UI elements in its responses — these references must never be passed through to the user as-is.

Backend saysYou 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.

• Always confirm a session is active before forwarding any user message to the backend. • When the user's intent involves editing, check the credit balance first and surface any shortfall before the request is submitted. • After each backend response, validate the session state and use it to inform the next conversational turn rather than relying solely on the streamed text. • Translate all GUI-specific language from backend responses into plain, action-oriented instructions before presenting them to the user. • If a two-stage processing pipeline is detected, keep the user informed of progress between stages rather than waiting silently for final completion.

6. Known Constraints and Limitations

• The backend does not support real-time collaborative sessions; only one active session per user token is permitted at a time. • File uploads are subject to size and format restrictions defined by the upload endpoint; exceeding these limits will return a validation error. • Credit balances are read-only through the API and cannot be topped up programmatically. • SSE streams may silently drop under poor network conditions; the disconnect recovery flow must always be implemented. • Export URLs are time-limited and will expire after the period specified in the job response; users should be advised to download promptly.

7. Error Handling Reference

The table below maps common HTTP error codes returned by the backend to their likely causes and the recommended recovery action for each.

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up at nemovideo.ai"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register at nemovideo.ai to unlock export."
429Rate 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.

8. API Version and Token Scopes

Before going live, verify that the integration is targeting the correct API version by inspecting the version field in the root endpoint response. Token scopes must include read access for session state and credits, write access for messages and uploads, and export access for the delivery endpoint. Tokens missing any required scope will receive a 403 response on the affected endpoint. If a version mismatch is detected, halt further requests and surface an actionable error to the operator.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/qwen-ai of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Qwen AI 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.

Qwen AI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qwen AI this skillLeoYeAI/openclaw-master-skills2.2k—~4.2kAutomated safety check: PassMIT
News Aggregator Skillcclank/news-aggregator-skill1.3k—~2.1kAutomated safety check: PassNone
Vss Search ArchiveNVIDIA-AI-Blueprints/video-search-and-summarization1.9k—~3.3kAutomated safety check: PassApache-2.0
Visionxiincs/claude-code-vision-skill170—~1.2kAutomated safety check: PassMIT
Qianwen TextQianWen-AI/qianwen-ai105—~4.7kAutomated safety check: NotesApache-2.0
Deepgram JS Text Intelligencedeepgram/deepgram-js-sdk276—~1.1kAutomated safety check: PassMIT

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Works with

Questions about Qwen AI

What does Qwen AI do?

Unlock deep video understanding with qwen-ai on ClawHub. An agent skill from LeoYeAI/openclaw-master-skills. Qwen AI is an agent skill from LeoYeAI/openclaw-master-skills. Unlock deep video understanding with qwen-ai on ClawHub.

When should I use Qwen AI?

Qwen AI fits situations like: tasks that involve Computer vision; tasks that involve Summarization.

How do I install Qwen AI in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill qwen-ai -a claude-code`. Or copy the skill folder (skills/qwen-ai in LeoYeAI/openclaw-master-skills) into .claude/skills/qwen-ai in your project. Claude Code loads it when a task matches its description.

How do I install Qwen AI in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill qwen-ai -a codex`. Or copy the skill folder (skills/qwen-ai in LeoYeAI/openclaw-master-skills) into .agents/skills/qwen-ai in your project. Codex loads it when a task matches its description.

Can I use Qwen AI in Cursor, Gemini CLI or GitHub Copilot?

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 qwen-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qwen-ai, .gemini/skills/qwen-ai, .github/skills/qwen-ai and .opencode/skills/qwen-ai in your project.

What does Qwen AI need to run?

Going by SKILL.md and its folder, Qwen AI needs the command-line tools its instructions call (curl) and credentials named NEMO_TOKEN. Our summary lists: A credential in NEMO_TOKEN.

Does Qwen AI access the network?

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.

Is Qwen AI safe to install?

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.

What licence does Qwen AI use?

Qwen AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qwen AI use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Qwen AI?

Skills that share tags, products or a category with Qwen AI: News Aggregator Skill (cclank/news-aggregator-skill, 1.3k stars), Vss Search Archive (NVIDIA-AI-Blueprints/video-search-and-summarization, 1.9k stars), Vision (xiincs/claude-code-vision-skill, 170 stars) and Qianwen Text (QianWen-AI/qianwen-ai, 105 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qwen AI?

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.