skills

In the author's own words, from each skill's SKILL.md.

• 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 performance of a MAX model, get tokens-per-second / TTFT / TPOT numbers, run a concurrency or request-rate s…

  benchmark-model/SKILL.md on GitHub (opens in a new tab)

• debug-model

  Debug silent corruption when a MAX model loads, compiles, serves, and generates tokens but 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 then diverges — during an architecture port, a quantization bring-up, a multi-GPU conv…

  debug-model/SKILL.md on GitHub (opens in a new tab)

• 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 correct answers, or running repeatable dataset evaluations against a MAX OpenAI-compatible endpoint.

  eval-model/SKILL.md on GitHub (opens in a new tab)

• 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 Hugging Face config and modeling code, pick the V2 graph or ModuleV3 lane, scaffold from a similar MAX architecture, implement each layer to match HF, serve, then verify against the Hugging Face reference. Wh…

  import-model/SKILL.md on GitHub (opens in a new tab)

• migrate-max-v2-to-v3

  Use when migrating a MAX model from the V2 graph API (max.nn, TensorValue, explicit Graph construction) to ModuleV3 (max.experimental.nn, Tensor, F.lazy() + compile()). Triggers on: "migrate to ModuleV3", "port a max.nn model to max.experimental", "convert TensorValue to Tensor", "update my model to the V3 API", "ModuleV3 migration". Workflow: read the concept map, rewrite imports and __call__ si…

  migrate-max-v2-to-v3/SKILL.md on GitHub (opens in a new tab)

• 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-gpu-fundamentals/SKILL.md on GitHub (opens in a new tab)

• 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 build Python extension modules in Mojo, wrap Mojo structs for Python consumption, or convert between P…

  mojo-python-interop/SKILL.md on GitHub (opens in a new tab)

• 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 Mojo code, translating projects to Mojo, or otherwise generating Mojo. Use this skill to overcome misconceptions with how Mojo is written.

  mojo-syntax/SKILL.md on GitHub (opens in a new tab)

• 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.

  new-modular-project/SKILL.md on GitHub (opens in a new tab)

• 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/rocprof/ncu trace of max serve," or wants to measure MAX inference performance. Works for any model M…

  profile-model/SKILL.md on GitHub (opens in a new tab)

• 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 model. Use this whenever the user wants to run, launch, start, or host a model on MAX, bring up an…

  serve-model/SKILL.md on GitHub (opens in a new tab)

No skill matches that filter.

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