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model-authoring

apple/coreai-modelsSkill

Empirical rules for authoring PyTorch models for on-device execution on Apple platforms, covering energy-efficient inference, scalable compute, and correctness testing. Use this skill whenever the user is writing, debugging, or reviewing PyTorch model code intended for on-device execution — even if they don't explicitly mention Neural Engine or Core AI. Covers BC1S layout, op compatibility, KV cache patterns, precision rules, PSNR verification, activation functions, and common issues.

ScannedSkillSource: GitHub
2,198 stars +17 this week Updated 16d ago License BSD-3-Clause Context ≈126 tokens always loaded
78popular

Why this score

Stars20/35
Usage (forks)8/15
Upkeep25/25
License15/15
Owner history10/10

This repo hosts 3 skills, so its 2,198 stars are split between them (about 733 each) for scoring.

Popularity score: 78/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

Security

Scanned Oct 21, 2026 at commit 82c3488537d8, with Cisco's open-source skill-scanner.

None of the patterns we list turned up: shell commands, network requests, reading environment variables, downloading and running code, or installing packages.

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

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