Qwen-MM-Plugins is a collection of plugins that gives agent harnesses native multimodal abilities, including reading images, video, documents, code, and data. It is used to add these capabilities to coding agents across several supported harnesses, either through local models or multimodal APIs. The catalogue entries are its independently installable skills, MCP servers, and setup instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add QwenLM/Qwen-MM-Plugins --skill video-translationgit clone --depth 1 https://github.com/QwenLM/Qwen-MM-PluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/qwenlm/qwen-mm-plugins/video-translation)<a href="https://agentmods.dev/skills/qwenlm/qwen-mm-plugins/video-translation"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-mm-plugins/video-translation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/qwenlm/qwen-mm-plugins/video-translation"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-mm-plugins/video-translation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.00570 |
| Opus 5 | $0.00032 | $0.00285 |
| Sonnet 5 | $0.00013 | $0.00114 |
| Haiku 4.5 | $0.00006 | $0.00057 |
Grade A, and why
qwen-mm-plugins-omni-chatcut-video-translation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Translation
Own one durable project and route it by state:
source video → Agent-reconciled Omni/VAD transcript → Agent-authored dubbing plan → dubbed render → Agent listening review
Inspect first:
python3 <skill-root>/scripts/inspect_video_translation_state.py <project-dir>
Use the first applicable route: review or validate an existing delivery; resume a plan/render; translate an accepted transcript; or analyze a new source. Read pipeline-contract.md before accepting artifacts and dubbing-service.md when configuring the external GPU service. Never infer success from filenames alone.
Internal workflows
- Source speech, subtitles, speakers, and timing: source-analysis/WORKFLOW.md
- Translation and duration-aware adaptation: translation-authoring/WORKFLOW.md
- Voice references, TTS, mix, remux, and QA: dubbing-rendering/WORKFLOW.md
Load only the current workflow. Reuse the bundled omni_call for audio-video understanding. Use the
video-translation MCP tools for the external dubbing service and deterministic local media execution.
Authorization and configuration
Analysis and translation-only targets stop before TTS. A full or resumed dubbing request authorizes calls
to the configured external dubbing service. The service URL comes from QWEN_MM_DUBBING_SERVER_URL. Never
write it to artifacts.
Do not use server-local paths as portable outputs. Tools upload local inputs and save returned audio into the project. Preserve the source video stream during final remux. A delivery is complete only after the final file fully decodes and the measured QA contract passes.
User-facing completion
After a successful render, surface the returned summary directly to the user. Report the segment count,
the number of automatic risk flags, and each segment that needs manual listening review with its time range,
translated text, and reason. Link full/translation_summary.md for a readable report and
full/translation_diagnostics.json for complete machine-readable details. Even when no automatic flags are
found, instruct the user to perform one end-to-end check for ordering, overlaps, pronunciation, and mix balance.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/manifest-template.json 610 B
- references/dubbing-service.md 1.7 KB
- references/launch_dubbing_server.py 31 KB runs code
- references/pipeline-contract.md 6.4 KB
- scripts/inspect_video_translation_state.py 762 B runs code
- workflows/dubbing-rendering/references/background-audio-review-prompt.md 1.3 KB
- workflows/dubbing-rendering/WORKFLOW.md 4.2 KB
- workflows/source-analysis/WORKFLOW.md 3.4 KB
- workflows/translation-authoring/WORKFLOW.md 3.2 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 51 lines · 64 tokens per session scan A 07f2e005d629
qwen-mm-plugins-omni-chatcut-video-translation is a skill published in the GitHub repository QwenLM/Qwen-MM-Plugins (2,814 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 570 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.
Other skills, from other repositories
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A service for sending audio or video to be dubbed into another language, checking the job's progress, and downloading the finished dubbed audio.