Task runner for
AI agents

Drop markdown files in a folder, number them, and run. Each file is one task sent to an AI agent. When you need loops, retries, or conditional logic — add an .ash script. Start simple. Grow as needed.

How it works GitHub

Deterministic Control, AI Execution

AI agents handle ambiguity — understanding intent, making judgments. They're bad at sequencing, branching, and retrying. Ash handles the structure. Agents handle the content.

Guaranteed Sequencing

Tasks run in numbered order every time. No "what should I do next?" — the script decides. The agent executes.

Bounded Autonomy

The agent decides how to do its step. Ash decides whether the step happens, how many times, and what comes next.

Repeatability

A weekly report, a recurring audit, a batch job — same process every time, even when the content of each step varies.

Execution Efficiency

Pre-determined control flow runs at CPU speed. AI time is spent only where it adds value — on the content of each step.

Workflows as Code

Review content, audit compliance, publish updates — all live in files you commit, version, share, and re-run. Not buried in chat threads.

Agent-Agnostic

OpenCode, Claude Code, Aider, or a custom tool. Define in a config file. Swap providers without touching your workflows.

How Ash Works

Drop markdown files in a folder, number them, and run. Each file is a task sent to an AI agent. Output flows between steps.

tasks/

Step 1: Create a folder of tasks 
tasks/
├── 01-research.md
├── 02-implement.md
├── 03-review.ash
└── 04-deploy.md

Terminal

Step 2: Run — agents execute each task in order
$ ash tasks/
[1/4] 01-research.md → opencode sonnet-4
[2/4] 02-implement.md → claude-code claude-sonnet-4
[3/4] 03-review.ash → aider claude-haiku-3
[4/4] 04-deploy.md → opencode haiku-flash
4 tasks, 4 passed

When You Need Full Orchestration

Markdown tasks handle simple agent calls. Drop in an .ash file when a single prompt isn't enough — variables, conditionals, shell commands within one step. Standalone scripts give you the full language: loops, retry, parallelism, functions. Same runtime, same state passing. Just add power as you need it.

Variables, Strings & Shell

MSG = "hello"
ITEMS = ["a", "b", "c"]
FIRST = ITEMS[0]
print "count: ${len(ITEMS)}"
working_dir = $(pwd)

Agent Calls

do "Review this code" with opencode

try {
  do "Fix the bug" with fixer
} fail {
  do "Retry: ${stderr}"
} upto 3

Control Flow

for FILE in FILES {
  do "Review ${FILE}"
  if $? != 0 { exit 1 }
}

exec npm test
if $? == 0 {
  print "all good"
}

Functions & Composition

fn review(path) {
  do "Review ${path}" with opencode
}

include "helpers.ash"
review("src/main.rs")

Playground

Write and run Ash scripts in your browser, or use the REPL for interactive experimentation. The built-in js-echo agent echoes your prompt back.

Script
Output Status: ready
Click "Run" to execute the script.
loading WASM...