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Hpc Toolchains

Organization
SciMate-AI
hpc-toolchains

Build, review, debug, and stabilize HPC compiler and build-toolchain workflows. Use when choosing compiler families such as GCC, Clang, or oneAPI; configuring CMake, `find_package`, or toolchain files; aligning BLAS or LAPACK or MPI stacks; using environment modules or Spack; or repairing ABI, link, and build-system failures.

Overview

PublisherSciMate-AI
RepositoryHPC-Skills
Skill namehpc-toolchains
Stars
97
Forks
10
Bundled files
15
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by SciMate-AI on GitHub. Read the source before you install it.

Installation

Install the Hpc Toolchains AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/SciMate-AI/HPC-Skills/tree/main/skills/hpc-toolchains
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SciMate-AI/HPC-Skills.git /tmp/HPC-Skills
mkdir -p .claude/skills
cp -r /tmp/HPC-Skills/skills/hpc-toolchains .claude/skills/hpc-toolchains
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hpc Toolchains in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hpc Toolchains on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hpc Toolchains is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

HPC Toolchains

Treat the toolchain as a coherent stack. Pick the compiler family, MPI family, math libraries, and build system together before tuning application-specific flags.

Start

  1. Read references/compiler-family-selection.md before choosing GCC, Clang, or vendor compilers.
  2. Read references/configure-and-build-matrix.md when deciding between CMake, Make, Ninja, or wrapper-driven builds.
  3. Read references/cmake-and-find-package-playbook.md when writing or repairing CMakeLists.txt, find_package, imported targets, or cache variables.
  4. Read references/toolchain-files-and-presets.md when the build depends on reusable compiler, MPI, or site configuration.
  5. Read references/build-type-and-abi-hygiene.md when debugging release versus debug mismatches, C++ standard mismatches, symbol issues, or ABI drift.
  6. Read references/blas-lapack-mpi-consistency.md when linking against BLAS, LAPACK, ScaLAPACK, MPI, or vendor math stacks.
  7. Read references/modules-and-spack-playbook.md when using environment modules, compiler wrappers, external packages, or Spack environments.
  8. Read references/error-recovery.md when configure, compile, link, or runtime-loader failures occur.

Work sequence

  1. Decide the stack boundary first:
    • site-provided modules
    • Spack environment
    • container image
    • user-local source build
  2. Pick one compiler family and keep the full dependency graph aligned to it.
  3. Decide how dependencies are discovered:
    • wrapper compilers
    • find_package
    • pkg-config
    • explicit include and library paths only as a last resort
  4. Keep build directories, cache state, and install prefixes separated by toolchain.
  5. Record the exact configure command before tuning warning or optimization flags.

Guardrails

  • Do not mix compiler and MPI families casually across one build tree.
  • Do not patch over a bad discovery path with many ad hoc include and library flags.
  • Do not treat ABI, C++ standard, and release or debug mode as cosmetic metadata.
  • Do not let one dependency come from a different module stack unless the site explicitly supports that mix.

Additional References

Load these on demand:

  • references/cmake-and-find-package-playbook.md for imported-target and cache-variable discipline
  • references/toolchain-files-and-presets.md for reusable site or cluster build configuration
  • references/build-type-and-abi-hygiene.md for symbol, ABI, and optimization mismatches
  • references/blas-lapack-mpi-consistency.md for math-library and MPI stack alignment
  • references/modules-and-spack-playbook.md for module and Spack-based reproducibility
  • references/error-pattern-dictionary.md for fast matching of common toolchain failure classes

Reusable Templates

Use assets/templates/ when a concrete starting point is faster than rebuilding the build stack from scratch, especially:

  • minimal-cmake-project/CMakeLists.txt
  • minimal-cmake-project/main.cpp
  • configure-gcc-openmpi.sh
  • build-smoke-slurm.sh
  • spack-env-minimal.yaml

Outputs

Summarize:

  • chosen compiler and MPI family
  • dependency-discovery method
  • build-system strategy
  • math-library and ABI alignment decisions
  • the exact failure phase if the workflow is being repaired

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hpc Toolchains AI skill do?

Build, review, debug, and stabilize HPC compiler and build-toolchain workflows. Use when choosing compiler families such as GCC, Clang, or oneAPI; configuring CMake, `find_package`, or toolchain files; aligning BLAS or LAPACK or MPI stacks; using environment modules or Spack; or repairing ABI, link, and build-system failures.

Why use Hpc Toolchains on TypingMind?

Because you install it once and use it with any model. Hpc Toolchains is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hpc Toolchains in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SciMate-AI/HPC-Skills/tree/main/skills/hpc-toolchains. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hpc Toolchains?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hpc Toolchains?

As many as you like. As long as a model supports skills, you can use Hpc Toolchains with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hpc Toolchains AI skill free?

Yes. It is published on GitHub by SciMate-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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