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 movie-commentarygit 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/movie-commentary)<a href="https://agentmods.dev/skills/qwenlm/qwen-mm-plugins/movie-commentary"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-mm-plugins/movie-commentary/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/movie-commentary"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-mm-plugins/movie-commentary.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 | $0.00063 | $0.00552 |
| Opus 5 | $0.00032 | $0.00276 |
| Sonnet 5 | $0.00013 | $0.00110 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
qwen-mm-plugins-omni-chatcut-movie-commentary 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Movie Commentary
Own one durable project and route it by state:
source movie → complete Omni evidence → validated plan → rendered shards → final commentary + QA
Inspect first:
python3 <skill-root>/scripts/inspect_movie_commentary_state.py <project-dir>
Use the first applicable route: validate an existing final delivery; resume incomplete shard execution; render a validated plan; author from complete source evidence; or analyze a new source. Never infer completion from filenames alone. Read pipeline-contract.md before accepting or invalidating artifacts.
Internal workflows
- Complete-film evidence: source-analysis/WORKFLOW.md
- Narration and edit plan: commentary-authoring/WORKFLOW.md
- TTS, shard rendering, assembly, and QA: rendering/WORKFLOW.md
Load only the workflow needed by current state. Use the capability's atomic MCP tools to initialize and probe a project, validate plans, freeze shards, and validate delivery. Use the named movie-commentary planner/executor agents when the harness exposes them; otherwise dispatch genuinely separate generic subagents with the corresponding workflow contract. Do not collapse both roles into one agent.
Project and authorization
Use manifest-template.json. A new project root must be empty. A non-empty root requires explicit resume intent. Full production authorizes the required Omni, TTS, and local render calls; analysis-only and plan-only targets stop before TTS/render. Credentials never enter artifacts.
The default Chinese voice is zh-CN-YunxiNeural at +20% with no additional atempo. Without a licensed
BGM manifest, BGM is none. Preserve source aspect ratio. Commentary subtitles must be measured against
the actual source subtitle band.
Completion
A final result requires every planned segment resolved, reports matching the frozen shard contract, full decode, audio/video duration agreement, expected frame count, measured loudness/true peak, black/freeze/ silence checks, seam inspection, subtitle placement, and original-dialogue highlight checks. Fake green is worse than a blocked project.
What ships with it
6 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.
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.
- 2d ago First seen · 52 lines · 63 tokens per session scan A 4e17b00675f5
qwen-mm-plugins-omni-chatcut-movie-commentary is a skill published in the GitHub repository QwenLM/Qwen-MM-Plugins (2,814 stars, last pushed yesterday), licensed Apache-2.0. It adds 63 tokens to every session and 552 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.
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