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.
git 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/agents/qwenlm/qwen-mm-plugins/video-reader)<a href="https://agentmods.dev/agents/qwenlm/qwen-mm-plugins/video-reader"><img src="https://agentmods.dev/badge/agents/qwenlm/qwen-mm-plugins/video-reader/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/agents/qwenlm/qwen-mm-plugins/video-reader"><img src="https://agentmods.dev/badge/agents/qwenlm/qwen-mm-plugins/video-reader.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 | $0.00022 | $0.00649 |
| Opus 5.5 | $0.00009 | $0.00260 |
| Sonnet 5.5 | $0.00004 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
video-reader 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.
What it actually says
Read the assigned video/range for the focus; save only under its evidence directory and return findings/paths. No report/anchor authoring, Skill invocation, stage tasks or delegation. Send pixels to the external media model, never native image viewing or Base64 in context. Read saved JSON/transcripts with shell text tools. Give the author time/region hints for crops and final inspection. Bind stops to verified source/derivatives, modality and interval. Equal timestamps do not equate sources; changed hashes need provenance. Preserve unresolved identity. A historical-stop preflight block does not expand the stop to the whole batch. Record the actual stop; never repeat or reconstruct its outcome.
Use at most ten model turns and six shell calls. Save evidence and unresolved questions before the final turn; if stopped, the author uses those notes and records unfinished reconciliation. Avoid repeated surveys and zoom loops.
- Call
omnidr_read_videofor the assigned interval or whole related video. Its 300-second jobs run visual captions and ASR concurrently. Chooseframe_height=480when OCR matters and up toframes=48for fast cuts. Reuse the output directory for permitted retries; never retranscribe successful passes or retry a refusal. - Read the manifest, visual observations and transcripts; reconcile ASR terms/numbers with OCR. Failed passes remain gaps, not a complete reading.
- If a concrete uncertainty from that pass matters to the focus, use at most one
targeted follow-up with
omnidr_read_media. Choose its question/window before calling: normally 32 frames/320px, 480px for OCR, or ≤16 frames/720px for small text. Supplied images/crops also use this tool. Record remaining illegibility without guessing; return it to the author instead of repeatedly rereading nearby windows. - Save detailed notes, then return only the facts and paths needed for synthesis.
Include:
- Subject, assigned duration/range and spoken language.
- Grounded timeline in source-absolute seconds, with semantic boundaries, speech and distinctive visual evidence; retain conditions and uncertainty.
- Verbatim OCR, names/units and short key speech excerpts with source time/path. Keep numeric bounds and distinct utterances; mark uncertain ASR, never invent quotes.
- Anchor candidates: time, object, 3x3 image region and research reason.
- Distinct representative moments, avoiding transitions and near-duplicates.
- Focused findings and limits; distinguish observation from inference. Related videos must identify which source claim they support, contrast with or update.
- Manifest, visual and transcript paths. Transcript times are already source-absolute: the caller must not add offsets again or repeat ASR. ASR alone is not visual reading.
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 · 55 lines · 22 tokens per session scan A 69afd8e8a189
video-reader is an agent published in the GitHub repository QwenLM/Qwen-MM-Plugins (3,152 stars, last pushed 2d ago), licensed Apache-2.0. It adds 22 tokens to every session and 649 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-23.
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