oh-my-pi

A coding agent with the IDE wired in. omp.sh

Built by Stencil Labs · Fork of Pi by @mariozechner

The most capable agent surface that ships. Continuously tuned by real-world use — complete out of the box, open all the way down.

60+ providers · 31 built-in tools · 14 lsp ops · 28 dap ops · ~80k lines of Rust core.

Note

Pull requests are temporarily open to everyone as a trial. We previously required a vouch before accepting PRs; that requirement is lifted for now while we evaluate how open contributions go. Depending on the results, the vouch system may return.

Install

macOS · Linux

curl -fsSL https://omp.sh/install | sh

Without a usable bun (or with --binary), the install scripts fetch the prebuilt binary from build.stencil.so and check its SHA-256 before installing it. Pin a release with curl -fsSL https://omp.sh/install | sh -s -- --binary --ref v (PowerShell: -Binary -Ref v).

Alpine / musl: the prebuilt musl binary links libstdc++/libgcc dynamically, which stock Alpine does not ship. Install them first: apk add libstdc++ libgcc.

Homebrew

brew install can1357/tap/omp

Bun (recommended)

bun install -g @oh-my-pi/pi-coding-agent

Nix

# Run without installing
nix run github:can1357/oh-my-pi

# Or install into the active profile (Nix < 2.30: `nix profile install`)
nix profile add github:can1357/oh-my-pi

Flake consumers can use packages..omp, overlays.default, nixosModules.default, or homeManagerModules.default. A Home Manager configuration can install OMP and own its settings declaratively:

{
  inputs.omp.url = "github:can1357/oh-my-pi";

  # In your Home Manager module:
  imports = [ inputs.omp.homeManagerModules.default ];
  programs.omp = {
    enable = true;
    settings.startup.quiet = true;
  };
}

Windows (PowerShell)

irm https://omp.sh/install.ps1 | iex

Pinned versions (mise)

mise use -g github:can1357/oh-my-pi

macOS · Linux · Windows · bun ≥ 1.3.14

Shell completions

omp generates its own completion scripts for bash, zsh, and fish from the live command/flag metadata, so they never drift from the actual CLI. Subcommands, flags, and enum values complete statically; model names (--model, --smol, --slow, --plan) resolve against the bundled model catalog and --resume against your on-disk sessions.

# zsh — add to ~/.zshrc (or write the output into a file on your $fpath)
eval "$(omp completions zsh)"

# bash — add to ~/.bashrc
eval "$(omp completions bash)"

# fish
omp completions fish > ~/.config/fish/completions/omp.fish

Every tool, benchmaxxed.

Edits that land on the first attempt. Reads that summarize files instead of dumping their content. Searches that return instantly. Pick any model — omp will get it right.

• read : summarized snippets · ideal defaults · selector hit rate

• grep : fastest in the west

• lsp : everything your IDE knows, the agent knows

• prompts : adjusted relentlessly for each model

Read the full post ↗

The Pi you love, with batteries included.

Originally built on Mario Zechner's wonderful Pi, omp adds everything you're missing.

01 · Code execution w/ tool-calling

Most harnesses give the agent a Python sandbox and call it done. Ours runs persistent Python and a Bun worker, and either kernel can call back into the agent's own tools — read, search, task — over a loopback bridge. The agent loads a CSV with tool.read from inside Python, charts it from JavaScript, and never leaves the cell.

02 · LSP wired into every write

Ask for a rename and you get a rename. The call goes through workspace/willRenameFiles, so re-exports, barrel files, and aliased imports update before the file moves. Everything your IDE knows, the agent knows.

Read the LSP config docs

03 · Drives a real debugger

A C binary segfaults: the agent attaches lldb, steps to the bad pointer, reads the frame. A Go service hangs: it attaches dlv and walks the goroutines. A Python process is wedged: debugpy, pause, inspect, evaluate. Most agents are still sprinkling print statements.

Watch the capture ↗

04 · Time-traveling stream rules

Your rules sit dormant until the model goes off-script. A regex match aborts the stream mid-token, injects the rule as a system reminder, and retries from the same point. You get course-correction without paying context tax on every turn. Injections survive compaction, so the fix sticks.

Watch the capture ↗

05 · First-class subagents

Split a job across workers and get typed results back. task fans out into isolated worktrees, each worker runs its own tool surface, and the final yield is a schema-validated object the parent reads directly. No prose to parse, no merge conflicts between siblings, no orphaned edits.

Watch the capture ↗

Watch the fan-out while it runs: Alt+A opens Agent Hub, where the roster shows current activity and usage for every subagent. Open one to read its live transcript, type a steering message, revive a parked worker, or kill a stuck one without aborting the parent session.

06 · A second model, watching every turn.

Pair a reviewer model to the 'advisor' role and it reads every turn the main agent takes, injecting notes inline — a quiet aside, a concern, or a hard blocker. It runs on its own context and its own model, so it catches what the doer rushed past. The main agent sees the note and course-corrects, or tells you why it won't.

Watch the capture ↗

07 · Hand someone the link, they're in.