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mojo-skills

Modular skills for writing Mojo, including GPU and Python interop

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Plugin mojo-skills from marketplace modular in modular/skills. Commands read from the repo's manifest — today.

What it installs

Skills (11)

  • benchmark-model

    Benchmark a model served on MAX with the `max benchmark` command: measure throughput (tokens/sec), latency (TTFT, TPOT, inter-token latency), and GPU utilization by driving load against a running `max serve` endpoint. Use this whenever the user wants to benchmark, load-test, or measure the performan

  • debug-model

    Debug a MAX model that loads, compiles, serves, and generates tokens but whose output disagrees with a reference implementation. Use whenever parity debugging stalls on scalar taps, the model returns gibberish or wrong greedy tokens, logit cosine is high but argmax differs, or generation is coherent

  • eval-model

    Measures the task accuracy of text models served by MAX using standard benchmarks such as GSM8K, MMLU, HellaSwag, ARC, AIME, GPQA, TruthfulQA, WinoGrande, and BABILong. Use when benchmarking a served model, comparing it with model-card or reference scores, verifying that a new MAX model produces cor

  • import-model

    Use when importing a new model architecture into MAX from a Hugging Face model ID. Triggers on: "import a model into MAX", "add model to MAX", "bring up <HF model> in MAX". Workflow: inspect the Hugging Face config and modeling code, then scaffold from a similar ModuleV3 architecture. Implement each

  • migrate-max-v2-to-v3

    Use when migrating a MAX model from the V2 graph API (max.nn.legacy, TensorValue, explicit Graph construction) to ModuleV3 (max.nn, Tensor, F.lazy() + compile()). Triggers on: "migrate to ModuleV3", "port a max.nn.legacy model to max.experimental", "convert TensorValue to Tensor", "update my model t

  • mojo-gpu-fundamentals

    The basics of how to program GPUs using Mojo. Use this skill in addition to mojo-syntax when writing Mojo code that targets GPUs or other accelerators. Use targeting code to NVIDIA, AMD, Apple silicon GPUs, or others. Use this skill to overcome misconceptions about how Mojo GPU code is written.

  • mojo-python-interop

    Aids in writing Mojo code that interoperates with Python using current syntax and conventions. Use this skill in addition to mojo-syntax when writing Mojo code that interacts with Python, calls Python libraries from Mojo, or exposes Mojo types/functions to Python. Also use when the user wants to bui

  • mojo-syntax

    Help to write Mojo code using current syntax and conventions. Always use this skill when writing any Mojo code, including when other Mojo-specific skills (e.g., mojo-gpu-fundamentals) also apply. Use when writing or reviewing Mojo code, translating projects to Mojo, or otherwise generating Mojo. Use

  • new-modular-project

    Creates a new Mojo or MAX project. Use when wanting to start a new Mojo or MAX project, initializing the `pixi` or `uv` environment to use Mojo or MAX, or when the user wants to begin a new Mojo or MAX project from scratch.

  • profile-model

    Profile a model running on MAX to find where it spends time and whether the GPU is saturated. Use when the user asks to "profile my model," "where is my model spending time," "why is inference slow," "is my GPU being utilized," "how much GPU am I using," "get a kernel breakdown," "capture an nsys/ro

  • serve-model

    Serve a model with MAX's `max serve` command: set up the environment (pixi or uv with the max-nightly conda channel / nightly wheel index), point the server at a Hugging Face repo or local checkpoint, target a custom architecture with `--custom-architectures`, and pick the right serve flags for the

View source on GitHub

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