MPI skill for distributed-memory parallel programming. An agent skill from mohitmishra786/low-level-dev-skills.

MITAuto-check passedDevelopment

Install Mpi

skills CLI
$ npx skills add mohitmishra786/low-level-dev-skills --skill mpi -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mohitmishra786/low-level-dev-skills mpi --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hpc/mpi .claude/skills/mpi && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
mpi
GitHub stars
253
Token cost
~1.4k tokens
SKILL.md length
235 words
Files
1
Skills in repo
138
Repo updated
First seen
Licence
MIT

At a glance

MPI skill for distributed-memory parallel programming. An agent skill from mohitmishra786/low-level-dev-skills.

  • Works in 9 steps: Minimal MPI program → Point-to-point → Collectives → …
  • Writing MPISend/Recv programs
  • SKILL.md covers Purpose, When to Use, Workflow and Common Problems, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mpi is an agent skill from mohitmishra786/low-level-dev-skills. MPI skill for distributed-memory parallel programming. Use when writing MPISend/Recv programs, collective operations, non-blocking communication, MPI+OpenMP hybrid, or debugging with mpirun. Activates on queries about MPIInit, MPIAllreduce, MPIIsend, mpirun, MPI-IO, or MPI performance.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Debugging. The repository describes itself as: A curated suite of AI agent skills for systems and low-level programming with C/C++, Rust, and Zig toolchains, covering compilers, debuggers, profilers, build systems…. The licence is MIT.

When your agent uses it

  • Writing MPISend/Recv programs
  • Collective operations
  • Non-blocking communication
  • MPI+OpenMP hybrid

Example prompts

  • “/mpi”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Minimal MPI program
  2. Point-to-point
  3. Collectives
  4. Non-blocking communication
  5. Subcommunicators
  6. MPI + OpenMP hybrid
  7. Launching with hostfile
  8. MPI-IO
  9. Performance issues

What it can do on your machine

Read from SKILL.md and the folder at commit bdc5847. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are c and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mpi loads about 1.4k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 235 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mohitmishra786/low-level-dev-skills at commit bdc5847, republished under its MIT licence (© mohitmishra786). 235 words, ~1,419 tokens.

Download SKILL.mdSave it as .claude/skills/mpi/SKILL.md (or your agent's skills folder).
name
mpi
description
MPI skill for distributed-memory parallel programming. Use when writing MPI_Send/Recv programs, collective operations, non-blocking communication, MPI+OpenMP hybrid, or debugging with mpirun. Activates on queries about MPI_Init, MPI_Allreduce, MPI_Isend, mpirun, MPI-IO, or MPI performance.

MPI

Purpose

Guide agents through MPI (Message Passing Interface) programming: point-to-point and collective communication, non-blocking operations, subcommunicators, MPI+OpenMP hybrid patterns, process launching with mpirun, debugging techniques, MPI-IO, and common performance issues.

When to Use

  • Parallelizing across multiple nodes or sockets
  • Implementing distributed algorithms (matrix decompose, FFT)
  • Combining MPI process parallelism with OpenMP thread parallelism
  • Running HPC jobs with Slurm/PBS + mpirun
  • Debugging deadlocks and message mismatches
  • Parallel file I/O with MPI-IO

Workflow

1. Minimal MPI program
c
#include <mpi.h>
#include <stdio.h>

int main(int argc, char **argv) {
    MPI_Init(&argc, &argv);

    int rank, size;
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
    MPI_Comm_size(MPI_COMM_WORLD, &size);

    printf("Hello from rank %d of %d\n", rank, size);

    MPI_Finalize();
    return 0;
}
bash
mpicc -o hello hello.c
mpirun -np 4 ./hello
# or
mpiexec -n 4 ./hello
2. Point-to-point
c
if (rank == 0) {
    int data = 42;
    MPI_Send(&data, 1, MPI_INT, 1, 0, MPI_COMM_WORLD);
} else if (rank == 1) {
    int recv;
    MPI_Recv(&recv, 1, MPI_INT, 0, 0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
    printf("rank 1 got %d\n", recv);
}

Tagged messages: match tag and source for MPI_Recv.

3. Collectives
c
int local = rank + 1;
int global_sum;

MPI_Allreduce(&local, &global_sum, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);

// Broadcast
if (rank == 0) data = 100;
MPI_Bcast(&data, 1, MPI_INT, 0, MPI_COMM_WORLD);

// Scatter/Gather
MPI_Scatter(sendbuf, sendcount, MPI_INT, recvbuf, recvcount, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Gather(sendbuf, sendcount, MPI_INT, recvbuf, recvcount, MPI_INT, 0, MPI_COMM_WORLD);
CollectivePurpose
MPI_BcastOne-to-all
MPI_ScatterDistribute chunks
MPI_GatherCollect chunks
MPI_AllreduceReduce + broadcast result
MPI_BarrierSynchronization
MPI_AlltoallAll-to-all exchange
4. Non-blocking communication
c
MPI_Request req;
MPI_Isend(buf, count, MPI_INT, dest, tag, MPI_COMM_WORLD, &req);
// overlap computation here
do_local_work();
MPI_Wait(&req, MPI_STATUS_IGNORE);

// Multiple requests
MPI_Request reqs[2];
MPI_Irecv(buf0, n, MPI_INT, 0, 0, comm, &reqs[0]);
MPI_Irecv(buf1, n, MPI_INT, 1, 0, comm, &reqs[1]);
MPI_Waitall(2, reqs, MPI_STATUSES_IGNORE);

Overlap communication with computation to hide latency.

5. Subcommunicators
c
int color = rank / 4;  // groups of 4
MPI_Comm subcomm;
MPI_Comm_split(MPI_COMM_WORLD, color, rank, &subcomm);

int subrank, subsize;
MPI_Comm_rank(subcomm, &subrank);
MPI_Comm_size(subcomm, &subsize);

MPI_Comm_free(&subcomm);
6. MPI + OpenMP hybrid
c
#pragma omp parallel
{
    int tid = omp_get_thread_num();
    // thread-local work on rank's data partition
}
MPI_Barrier(MPI_COMM_WORLD);
MPI_Allreduce(...);
bash
export OMP_NUM_THREADS=4
mpirun -np 8 --bind-to core ./hybrid_app
# 8 ranks × 4 threads = 32 cores

Bind ranks to sockets with --map-by ppr:2:socket.

7. Launching with hostfile
bash
# hostfile:
# node0 slots=4
# node1 slots=4

mpirun -np 8 --hostfile hosts.txt ./app

# Slurm integration
srun -n 64 ./app
# or
mpirun -np $SLURM_NTASKS ./app
bash
# Debug: tag output by rank
mpirun -np 4 --tag-output ./app

# Sequential debug (one rank at a time)
mpirun -np 4 -gdb ./app
8. MPI-IO
c
#include <mpi.h>

MPI_File fh;
MPI_File_open(MPI_COMM_WORLD, "output.dat",
    MPI_MODE_CREATE | MPI_MODE_WRONLY, MPI_INFO_NULL, &fh);

MPI_Offset offset = rank * chunk_size;
MPI_File_write_at(fh, offset, buf, count, MPI_DOUBLE, MPI_STATUS_IGNORE);

MPI_File_close(&fh);

Collective I/O for better performance:

c
MPI_File_write_at_all(fh, offset, buf, count, MPI_DOUBLE, MPI_STATUS_IGNORE);
9. Performance issues
Common bottlenecks
├── Load imbalance → dynamic scheduling (OpenMP) or redistribute MPI chunks
├── Serialization at rank 0 → tree-based reduce, parallel I/O
├── Excessive sync → replace Barrier with point-to-point where possible
├── Small messages → aggregate; use MPI_Pack or larger blocks
└── Alltoall on large process counts → consider MPI neighborhood collectives
bash
# MPI profiling
mpiP  # lightweight profiler
# or IPM, TAU MPI wrappers

Common Problems

SymptomCauseFix
Hang at MPI_RecvTag/source mismatchCheck Send/Recv pairing; use MPI_ANY_TAG debug
DeadlockCircular waitReorder comm pattern; use non-blocking
Wrong result in AllreduceWrong datatype/countVerify MPI_INT vs MPI_DOUBLE
Poor scalingRank 0 bottleneckDistribute I/O and aggregation
MPI_ERR_TRUNCATEReceive buffer too smallMatch send/recv counts
Hybrid oversubscriptionToo many threads×ranksOMP_NUM_THREADS = cores/ranks
  • skills/hpc/openmp — thread-level parallelism within MPI ranks
  • skills/hpc/rdma-verbs — low-latency interconnect under MPI
  • skills/allocators/numa-programming — bind ranks to NUMA nodes
  • skills/profilers/linux-perf — profile MPI rank hotspots
  • skills/debuggers/gdb — debug individual MPI processes
  • skills/compilers/gcc — MPI compiler wrapper flags

© mohitmishra786, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/hpc/mpi of mohitmishra786/low-level-dev-skills.

Open the folder on GitHubat commit bdc5847

Compare with similar skills

Mpi next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Mpi compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Mpi this skillmohitmishra786/low-level-dev-skills253—~1.4kAutomated safety check: PassMIT
Trellis Session Insightmindfold-ai/Trellis15k4 repos~1.7kAutomated safety check: PassAGPL-3.0
Native Data FetchingCherryHQ/cherry-studio-app4k6 repos~2.9kAutomated safety check: NotesMIT
Debugging Executionsn8n-io/n8n207k—~2.6kAutomated safety check: PassCustom licence
Aoti Debugpytorch/pytorch104k1 repos~1.7kAutomated safety check: PassCustom licence
Herdr Throwaway Reproductionherdrdev/herdr43k—~2.4kAutomated safety check: PassApache-2.0

Similar skills

  • Trellis Session Insight

    mindfold-ai/Trellis

    Reach into past AI conversation history through the trellis mem CLI.

    15k GitHub starsUsed in 4 repos~1.7k tokens
    DevelopmentAuto-check passed
  • Native Data Fetching

    CherryHQ/cherry-studio-app

    A skill your agent uses when implementing or debugging ANY network request, API call, or data fetching.

    4k GitHub starsUsed in 6 repos~2.9k tokens
    DevelopmentAuto-check: notes
  • Official

    Debug failed or wrong-output workflow executions using executions tools.

    207k GitHub stars~2.6k tokensUpdated today
    DevelopmentAuto-check passed
  • Aoti Debug

    pytorch/pytorch

    Debug AOTInductor (AOTI) errors and crashes. An agent skill from pytorch/pytorch.

    104k GitHub starsUsed in 1 repo~1.7k tokens
    DevelopmentAuto-check passed
  • Runs a disposable, uniquely named Herdr session inside an existing one so runtime, pane, terminal or API bugs can be reproduced without touching the main session.

    43k GitHub stars~2.4k tokensUpdated today
    DevelopmentAuto-check passed
  • Systematic Debugging

    ultralisp/ultralisp

    A skill your agent uses when encountering any bug, test failure, or unexpected behavior, before proposing fixes

    258 GitHub starsUsed in 51 repos~2.4k tokens
    DevelopmentAuto-check passed

More from mohitmishra786/low-level-dev-skills

All 138 skills in this repo
  • ARM and AArch64 Assembly

    mohitmishra786/low-level-dev-skills

    Guides reading and writing AArch64 and ARM Thumb assembly: compiler output, inline asm, registers, the AAPCS calling convention and NEON or SVE basics.

    253 GitHub stars~1.9k tokensUpdated 3 mo ago
    Auto-check passed
  • RISC-V Assembly Guide

    mohitmishra786/low-level-dev-skills

    Reference for RISC-V assembly on RV32 and RV64: register names and calling convention, extension naming, GCC and Clang inline asm, and QEMU with GDB debugging.

    253 GitHub stars~1.8k tokensUpdated 3 mo ago
    Auto-check passed
  • x86-64 Assembly Reference

    mohitmishra786/low-level-dev-skills

    Explains x86-64 registers, the System V AMD64 calling convention, and how to read compiler-generated or inline assembly.

    253 GitHub stars~1.5k tokensUpdated 3 mo ago
    Auto-check passed
  • Bazel for C and C++

    mohitmishra786/low-level-dev-skills

    Guides your agent through Bazel for C/C++ projects: BUILD files, Bzlmod dependencies, toolchain registration, remote execution, dependency queries and sandbox debugging.

    253 GitHub stars~1.5k tokensUpdated 3 mo ago
    Auto-check passed
  • Binary Hardening

    mohitmishra786/low-level-dev-skills

    Binary hardening skill for security-hardened C/C++ builds. An agent skill from mohitmishra786/low-level-dev-skills.

    253 GitHub stars~2k tokensUpdated 3 mo ago
    Auto-check passed
  • Binutils

    mohitmishra786/low-level-dev-skills

    GNU binutils skill for binary manipulation and analysis. An agent skill from mohitmishra786/low-level-dev-skills.

    253 GitHub stars~1.2k tokensUpdated 3 mo ago
    Auto-check passed

Categories

Questions about Mpi

What does Mpi do?

MPI skill for distributed-memory parallel programming. An agent skill from mohitmishra786/low-level-dev-skills. Mpi is an agent skill from mohitmishra786/low-level-dev-skills. MPI skill for distributed-memory parallel programming.

When should I use Mpi?

Mpi fits situations like: writing MPISend/Recv programs; collective operations; non-blocking communication; MPI+OpenMP hybrid.

How do I install Mpi in Claude Code?

Run `npx skills add mohitmishra786/low-level-dev-skills --skill mpi -a claude-code`. Or copy the skill folder (skills/hpc/mpi in mohitmishra786/low-level-dev-skills) into .claude/skills/mpi in your project. Claude Code loads it when a task matches its description.

How do I install Mpi in Codex?

Run `npx skills add mohitmishra786/low-level-dev-skills --skill mpi -a codex`. Or copy the skill folder (skills/hpc/mpi in mohitmishra786/low-level-dev-skills) into .agents/skills/mpi in your project. Codex loads it when a task matches its description.

Can I use Mpi in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitmishra786/low-level-dev-skills --skill mpi -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mpi, .gemini/skills/mpi, .github/skills/mpi and .opencode/skills/mpi in your project.

What does Mpi need to run?

SKILL.md names no scripts, command-line tools or credentials: Mpi is instructions for the agent only.

Does Mpi access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Mpi safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Mpi use?

Mpi is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mpi use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mpi?

Skills that share tags, products or a category with Mpi: Trellis Session Insight (mindfold-ai/Trellis, 15k stars), Native Data Fetching (CherryHQ/cherry-studio-app, 4k stars), Debugging Executions (n8n-io/n8n, 207k stars) and Aoti Debug (pytorch/pytorch, 104k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mpi?

mohitmishra786 (a GitHub user) maintains it in mohitmishra786/low-level-dev-skills, which has 253 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on June 27, 2026.

Source: mohitmishra786/low-level-dev-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.