Agent skill

Coding Mojo

by oaustegard in oaustegard/claude-skills

Develop and run Mojo code in Claude.ai containers. An agent skill from oaustegard/claude-skills.

MITAuto-check passed

Install Coding Mojo

skills CLI
$ npx skills add oaustegard/claude-skills --skill coding-mojo -a claude-code

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

GitHub CLI
$ gh skill install oaustegard/claude-skills coding-mojo --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/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/coding-mojo .claude/skills/coding-mojo && 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
coding-mojo
GitHub stars
150
Token cost
~1.6k tokens
SKILL.md length
482 words
Files
3
Skills in repo
93
Repo updated
First seen
Licence
MIT

At a glance

Develop and run Mojo code in Claude.ai containers. An agent skill from oaustegard/claude-skills.

  • Writing Mojo code
  • SKILL.md covers Installation, Running Mojo Code, Critical Syntax Corrections… and Companion Skills (Modular…, plus 2 more sections
  • Calls uv, curl and python3; reaches api.github.com; needs GH_TOKEN
  • Benchmarking Mojo vs Python

What it does

Coding Mojo is an agent skill from oaustegard/claude-skills. Develop and run Mojo code in Claude.ai containers. Handles installation, compilation, and execution. Use when writing Mojo code, benchmarking Mojo vs Python, or when user mentions Mojo, Modular, or MAX. Routes to Modular's official skills (mojo-syntax, mojo-python-interop, mojo-gpu-fundamentals) for language-specific correction layers.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `CHANGELOG.md` and `README.md`).

It works with Python. The repository describes itself as: My collection of Claude skills. The licence is MIT.

When your agent uses it

  • Writing Mojo code
  • Benchmarking Mojo vs Python
  • User mentions Mojo

Example prompts

  • “/coding-mojo”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 559a6cd. 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

    Shell commands in SKILL.md call:

    • uv
    • curl
    • python3

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.github.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GH_TOKEN

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

Context cost

Coding Mojo loads about 1.6k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 482 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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 oaustegard/claude-skills at commit 559a6cd, republished under its MIT licence (© oaustegard). 482 words, ~1,561 tokens.

Download SKILL.mdSave it as .claude/skills/coding-mojo/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
coding-mojo
description
Develop and run Mojo code in Claude.ai containers. Handles installation, compilation, and execution. Use when writing Mojo code, benchmarking Mojo vs Python, or when user mentions Mojo, Modular, or MAX. Routes to Modular's official skills (mojo-syntax, mojo-python-interop, mojo-gpu-fundamentals) for language-specific correction layers.
metadata.version
0.2.1

Mojo Development in Claude.ai Containers

Mojo is a systems programming language from Modular that combines Python-like syntax with C-level performance. This skill handles container setup and execution. For language syntax and semantics, defer to Modular's official skills at github.com/modular/skills — they are authoritative correction layers for pretrained knowledge.

Installation

Install once per session (~20s via uv, ~500MB). Skip if already installed.

bash
if mojo --version 2>/dev/null; then
  echo "Mojo already installed"
else
  # Compiler binary without ML extras (~350MB saved)
  uv pip install --system --break-system-packages modular --no-deps 2>&1 | tail -5
  # Entry points + base deps (numpy, pyyaml, rich)
  uv pip install --system --break-system-packages mojo max 2>&1 | tail -5
  mojo --version
fi

Verify:

bash
echo 'def main(): print("Mojo ready")' > /tmp/_verify.mojo && mojo /tmp/_verify.mojo

Running Mojo Code

Quick tests (write to temp file):

bash
cat > /tmp/test.mojo << 'EOF'
def main():
    print("hello")
EOF
mojo /tmp/test.mojo

File execution (JIT compile + run, ~1.4s overhead):

bash
cat > /home/claude/example.mojo << 'EOF'
def main():
    print("Hello from Mojo")
EOF
mojo /home/claude/example.mojo

Build binary (for benchmarking — ~6s cold compile, but binary runs at native speed):

bash
mojo build /home/claude/example.mojo -o /home/claude/example
/home/claude/example

Use mojo build for benchmarks — mojo (JIT) includes ~1.4s compilation overhead per run. There is no mojo -e flag; always write to a file.

Critical Syntax Corrections (v26.2)

Pretrained models generate outdated Mojo. These corrections are current as of Mojo 26.2:

Wrong (pretrained)Correct (26.2)Notes
fn main():def main():fn is deprecated; def is the only function keyword
let x = 5var x = 5let removed; var for all bindings
inout selfmut self / out selfmut for mutation, out for __init__
@parameter forcomptime forCompile-time loops
List[Int](1, 2, 3)[1, 2, 3]Collection literals
from math import sqrtfrom std.math import sqrtstd. prefix required for all stdlib modules
from time import Xfrom std.time import XIncludes perf_counter_ns, sleep, etc.
__str__ / Stringablewrite_to / WritableString conversion protocol
String(self.x) for int→strString(self.x)This one is actually correct, but str() is not
list.append(item)list.append(item^)Non-copyable types require ^ transfer operator
var x: Int = perf_counter_ns()var x: UInt = perf_counter_ns()Time functions return UInt, not Int
Implicit copy of List[T].copy() or ^ transferList is not implicitly copyable; use explicit copy or move
Show full SKILL.md (210 more words)Show less

Companion Skills (Modular Official)

These skills from github.com/modular/skills provide deep syntax correction layers. If they are installed in the user's skill set, read them before writing Mojo code:

  • mojo-syntax — Comprehensive syntax corrections, type system, ownership model. Always use when writing any Mojo code.
  • mojo-python-interop — Calling Python from Mojo, type conversion, extension modules. Use when mixing Mojo and Python.
  • mojo-gpu-fundamentals — GPU programming (no CUDA syntax — Mojo has its own model). Reference only in Claude.ai containers (no GPU available).
  • new-modular-project — Project scaffolding with Pixi or uv. Use when starting a new Mojo/MAX project locally.

If companion skills are not installed, the correction table above covers the most common pretrained errors. For deeper work, fetch the skill content directly:

bash
curl -sL -H "Authorization: token $GH_TOKEN" \
  -H "Accept: application/vnd.github.v3.raw" \
  "https://api.github.com/repos/modular/skills/contents/mojo-syntax/SKILL.md?ref=main"

Container Constraints

  • No GPU: Claude.ai containers are CPU-only. GPU skills are reference material for generating code the user will run locally.
  • Session-ephemeral: Mojo installation doesn't persist across conversations. Reinstall each session.
  • Build artifacts: Store in /home/claude/. Copy final outputs to /mnt/user-data/outputs/.
  • Timeout: Long compilations or benchmarks may hit the ~200s bash timeout. Break work into smaller units.

Benchmarking Pattern

Compare Mojo vs Python on the same algorithm:

bash
# Python baseline
python3 -c "
import time
def fib(n):
    a, b = 0, 1
    for _ in range(n):
        a, b = b, a + b
    return a
# Warmup + timed runs
fib(90)
times = []
for _ in range(100):
    start = time.perf_counter()
    fib(90)
    times.append((time.perf_counter() - start) * 1e6)
import statistics
print(f'Python: median={statistics.median(times):.1f} µs, min={min(times):.1f} µs')
"

# Mojo version
cat > /home/claude/fib.mojo << 'EOF'
from std.time import perf_counter_ns

def fib(n: Int) -> Int:
    var a = 0
    var b = 1
    for _ in range(n):
        var tmp = a
        a = b
        b = tmp + b
    return a

def main():
    # Warmup
    _ = fib(90)
    
    # Timed runs
    var total_ns: UInt = 0
    var min_ns: UInt = 999999999
    for _ in range(100):
        var start = perf_counter_ns()
        _ = fib(90)
        var elapsed = perf_counter_ns() - start
        total_ns += elapsed
        if elapsed < min_ns:
            min_ns = elapsed
    print("Mojo: mean =", total_ns // 100, "ns, min =", min_ns, "ns")
EOF
mojo build /home/claude/fib.mojo -o /home/claude/fib
/home/claude/fib

Expected: Mojo is ~50x faster than CPython on tight numeric loops. SIMD and parallelism widen the gap further but require mojo-syntax and mojo-gpu-fundamentals skills for correct usage.

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

Files

SKILL.md and 2 other files in coding-mojo of oaustegard/claude-skills.

  • SKILL.md
  • CHANGELOG.md
  • README.md

Open the folder on GitHubat commit 559a6cd

Compare with similar skills

Coding Mojo 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.

Coding Mojo compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Coding Mojo this skilloaustegard/claude-skills150—~1.6kAutomated safety check: PassMIT
MCP Server Builderanthropics/skills180k62 repos~2.3kAutomated safety check: PassApache-2.0
PDF Processinganthropics/skills180k48 repos~2kAutomated safety check: PassProprietary
NotebookLM Research AssistantPleasePrompto/notebooklm-skill7.8k13 repos~2.4kAutomated safety check: NotesMIT
Manim Video Productionbrowser-use/video-use28k6 repos~3kAutomated safety check: PassMIT
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Works with

Questions about Coding Mojo

What does Coding Mojo do?

Develop and run Mojo code in Claude.ai containers. An agent skill from oaustegard/claude-skills. Coding Mojo is an agent skill from oaustegard/claude-skills.ai containers.

When should I use Coding Mojo?

Coding Mojo fits situations like: writing Mojo code; benchmarking Mojo vs Python; user mentions Mojo.

How do I install Coding Mojo in Claude Code?

Run `npx skills add oaustegard/claude-skills --skill coding-mojo -a claude-code`. Or copy the skill folder (coding-mojo in oaustegard/claude-skills) into .claude/skills/coding-mojo in your project. Claude Code loads it when a task matches its description.

How do I install Coding Mojo in Codex?

Run `npx skills add oaustegard/claude-skills --skill coding-mojo -a codex`. Or copy the skill folder (coding-mojo in oaustegard/claude-skills) into .agents/skills/coding-mojo in your project. Codex loads it when a task matches its description.

Can I use Coding Mojo 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 oaustegard/claude-skills --skill coding-mojo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/coding-mojo, .gemini/skills/coding-mojo, .github/skills/coding-mojo and .opencode/skills/coding-mojo in your project.

What does Coding Mojo need to run?

Going by SKILL.md and its folder, Coding Mojo needs the command-line tools its instructions call (uv, curl and python3) and credentials named GH_TOKEN. Our summary lists: Python 3.

Does Coding Mojo access the network?

SKILL.md names 1 domain. In commands or code: api.github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Coding Mojo 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 Coding Mojo use?

Coding Mojo 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 Coding Mojo use?

About 1.6k tokens (SKILL.md is roughly 6.2k 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 Coding Mojo?

Skills that share tags, products or a category with Coding Mojo: MCP Server Builder (anthropics/skills, 180k stars), PDF Processing (anthropics/skills, 180k stars), NotebookLM Research Assistant (PleasePrompto/notebooklm-skill, 7.8k stars) and Manim Video Production (browser-use/video-use, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coding Mojo?

oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 2, 2026.

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