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 ShuiHan268/dsh-qwen-mm-plugins --skill qwen-mm-plugins-apigit clone --depth 1 https://github.com/ShuiHan268/dsh-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/shuihan268/dsh-qwen-mm-plugins/qwen-mm-plugins-api)<a href="https://agentmods.dev/skills/shuihan268/dsh-qwen-mm-plugins/qwen-mm-plugins-api"><img src="https://agentmods.dev/badge/skills/shuihan268/dsh-qwen-mm-plugins/qwen-mm-plugins-api/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/shuihan268/dsh-qwen-mm-plugins/qwen-mm-plugins-api"><img src="https://agentmods.dev/badge/skills/shuihan268/dsh-qwen-mm-plugins/qwen-mm-plugins-api.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 | $0.00110 | $0.01611 |
| Opus 5 | $0.00055 | $0.00805 |
| Sonnet 5 | $0.00022 | $0.00322 |
| Haiku 4.5 | $0.00011 | $0.00161 |
Grade A, and why
qwen-mm-plugins-api 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 11d ago.
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.
This is a copy
100% identical to qwen-mm-plugins-api — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qwen-MM-Plugins API
You have qwen-mm-plugins-api MCP tools available. They call external models/services to understand media, grouped by model family:
- VL model (Qwen-VL, OpenAI-compatible endpoint):
vision_chat,ocr,grounding. - Omni model (Qwen-Omni — reads video frames and the embedded audio track together, so one call reasons over both):
omni_asr,omni_asr_timestamped,omni_multi_speaker_asr,omni_av_caption,omni_av_grounding,omni_av_counting,omni_music_caption. - Other services:
transcribe_audio(Qwen3-ASR),segmentation(a SAM3 server).
Prefer these over manual ffmpeg/ffprobe scripting. Check the qwen-mm-plugins-api tools in your tool list for full schemas and parameters.
When to Use Which Tool
VL model (single images/videos, spatial reasoning):
- Ask a VLM about images/videos (caption, VQA, free-form) →
vision_chat - Extract text from an image →
ocr - Detect/locate objects in an image (bounding boxes, spatial WHERE) →
grounding
Omni model (audio + video together, temporal reasoning; clips up to a few minutes):
- Transcribe speech, plain text →
omni_asr(one continuous string, no timestamps) - Transcribe with timestamps →
omni_asr_timestamped(granularity=sentenceorword; also returns SRT) - Who said what →
omni_multi_speaker_asr(diarization: speaker labels + timestamps + SRT; passnum_speakersif known) - Describe the content over time →
omni_av_caption(splits into spans, one description + start/end per span) - Find WHEN something happens →
omni_av_grounding(natural-languagequery→ matching time segments; temporal localization) - Count how many times an event/object/action occurs →
omni_av_counting(target→ total + per-occurrence timestamps) - Analyze / caption a music track →
omni_music_caption(whole-track tags — genre / moods / instruments / key / time signature / vocal profile — plus a dense English caption for music generation; audio-only, no timestamps)
What ships with it
1 file 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.
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.
- 11d ago First seen · 65 lines · 110 tokens per session scan A 27f8910080d3
qwen-mm-plugins-api is a skill published in the GitHub repository ShuiHan268/dsh-qwen-mm-plugins (3 stars, last pushed 25d ago), licensed Apache-2.0. It adds 110 tokens to every session and 1,611 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to qwen-mm-plugins-api, differing in 34 lines, and is treated as a copy.
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