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 wzyn20051216/matlab-agent-skills --skill matlab-signal-vision-aigit clone --depth 1 https://github.com/wzyn20051216/matlab-agent-skillsWrote 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/wzyn20051216/matlab-agent-skills/matlab-signal-vision-ai)<a href="https://agentmods.dev/skills/wzyn20051216/matlab-agent-skills/matlab-signal-vision-ai"><img src="https://agentmods.dev/badge/skills/wzyn20051216/matlab-agent-skills/matlab-signal-vision-ai/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/wzyn20051216/matlab-agent-skills/matlab-signal-vision-ai"><img src="https://agentmods.dev/badge/skills/wzyn20051216/matlab-agent-skills/matlab-signal-vision-ai.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 | $0.00068 | $0.00389 |
| Opus 5 | $0.00034 | $0.00195 |
| Sonnet 5 | $0.00014 | $0.00078 |
| Haiku 4.5 | $0.00007 | $0.00039 |
Grade A, and why
matlab-signal-vision-ai 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 12d 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
MATLAB Signal Vision AI
Use this skill when the core artifact is a processed signal, image, video, point cloud, neural network, or AI experiment.
Workflow
- Identify data modality, sampling rate, image size, color space, labels, and expected outputs.
- Confirm toolbox availability before using specialized APIs.
- Build a tiny reproducible subset first.
- Save intermediate outputs so failures are inspectable.
- Validate with numerical metrics, visual artifacts, and data shape checks.
Preferred APIs
- Signal:
designfilt,filter,spectrogram,pwelch,findpeaks, wavelet functions. - Vision:
imread,im2gray,imresize,imbinarize,regionprops,detectSURFFeatures,bboxOverlapRatio. - Deep learning:
dlnetwork,trainnet, datastores,minibatchqueue, pretrained models when licensed. - Lidar/medical imaging: use domain importers and viewers when available; keep metadata.
Validation
Choose relevant checks:
- Signal-to-noise ratio, peak frequency, filter stability.
- Image dimensions, pixel range, mask area, IoU, accuracy, F1.
- Training loss decreases on a smoke subset.
- Inference output has expected class names, boxes, or mask shape.
- Exported figure or video is nonempty.
Reproducibility
Record random seed, split policy, pretrained model version, GPU availability, and dataset hash or URL.
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.
- 12d ago First seen · 38 lines · 68 tokens per session scan A 502d40afef4b
matlab-signal-vision-ai is a skill published in the GitHub repository wzyn20051216/matlab-agent-skills (25 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 389 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 2026-08-30.
Other skills, from other repositories
digital-health-clinical-asr-eval
Stage 3 of Clinical ASR Flywheel. Score a NeMo manifest, produce the five-section KER leaderboard (by-ipasource diagnostic). Not for ASR auth (/riva-asr).
digital-health-clinical-asr-finetune
Stage 4 of the Clinical ASR Flywheel. Use when priority KER is above 0.3 to run stock NeMo SFT on Parakeet TDT v2 and offline cycle N+1 re-eval. NOT for generic word boosting (use /finetune-asr).
nemo-mbridge-perf-expert-parallel-overlap
Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlapmoeexpertparallelcomm, delaywgradcompute, and flex dispatcher backends such as DeepEP and HybridEP.
i4h-workflow-dataset-annotate
Grade or filter workflow HDF5 episodes with an OpenAI-compatible vision model. Use for visual success labels; do not use for replay, policy evaluation, or recordings without frames.
i4h-workflow-dataset-convert
Convert workflow HDF5 recordings to LeRobot datasets for training or browser inspection. Use for conversion; do not use for replay, augmentation, or raw-data repair.
i4h-lerobot-viz
Serve and visually inspect a converted LeRobot dataset in the browser. Use for videos and state/action timelines; do not use for raw workflow HDF5 or incomplete conversion output.