# R Mirai

Help users write correct R code for async, parallel, and distributed computing using...

- Repository: https://github.com/posit-dev/skills (551 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-10-28
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add posit-dev/skills --skill r-mirai -g -a claude-code -y`
Codex: `npx skills add posit-dev/skills --skill r-mirai -g -a codex -y`
Cursor: `npx skills add posit-dev/skills --skill r-mirai -g -a cursor -y`
Gemini CLI: `npx skills add posit-dev/skills --skill r-mirai -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add posit-dev/skills`

## Description

Help users write correct R code for async, parallel, and distributed computing using mirai. Use when users need to run R code asynchronously or in parallel, write mirai code with correct dependency passing, set up parallel workers, convert from future or parallel, use mirai_map, integrate with Shiny or promises, or configure cluster/HPC computing.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

mirai is a minimalist R framework for async, parallel, and distributed evaluation, built on nanonext.

## Core Principle: Explicit Dependency Passing

mirai evaluates expressions in a **clean environment** on a daemon process. Nothing from the calling environment is available unless passed explicitly, this is the #1 source of mistakes.

```r
# WRONG: my_data and my_func are not available on the daemon
m <- mirai(my_func(my_data))
```

There are two ways to pass objects, and the names used **must match** the names referenced in the expression.

### `.args` (recommended)

Objects in `.args` populate the expression's **local evaluation environment**, available directly by name inside the expression.

```r
m <- mirai(my_func(my_data), .args = list(my_func = my_func, my_data = my_data))
```

### `...` (dot-dot-dot)

Objects passed via `...` are assigned to the **daemon's global environment**. Use this when objects need to be found by R's standard scoping rules (e.g., helper functions called by other functions).

```r
m <- mirai(my_func(my_data), my_func = my_func, my_data = my_data)
```

### Shortcut: pass the whole calling environment

```r
# .args form, populates local eval env
process <- function(x, y) mirai(x + y, .args = environment())

# ... form, single unnamed environment, populates daemon global env
df_matrix <- function(x, y) mirai(as.matrix(rbind(x, y)), environment())
```

### When to use which

| Scenario | Use |
|----------|-----|
| Data and simple functions | `.args` |
| Helper functions called by other functions that need lexical scoping | `...` |
| Pass entire local scope to local eval env | `.args = environment()` |
| Pass entire local scope to daemon global env | `mirai(expr, environment())` |
| Large objects shared across many tasks | `everywhere()` first, then reference by name |

## Common Mistakes

### Unqualified package functions

Daemons start with no user packages loaded. Same applies inside `mirai_map()` callbacks.

The rest: https://github.com/posit-dev/skills/blob/HEAD/r-lib/r-mirai/SKILL.md