oh-my-pi

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  <img src="https://github.com/can1357/oh-my-pi/blob/main/assets/hero.png?raw=true" alt="omp">
</p>

<p align="center">
  <strong>A coding agent with the IDE wired in.</strong>
  <strong><a href="https://omp.sh">omp.sh</a></strong>
</p>

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<p align="center">
  Fork of <a href="https://github.com/badlogic/pi-mono">Pi</a> by <a href="https://github.com/mariozechner">@mariozechner</a> 
</p>

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

**40+** providers · **32** built-in tools · **14** lsp ops · **28** dap ops · **~55k** lines of Rust core.

## Install

**macOS · Linux**

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

**Homebrew**

```sh
brew install can1357/tap/omp
```

**Bun (recommended)**

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

**Windows (PowerShell)**

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

**Pinned versions (mise)**

```sh
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.

```sh
# 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.

| model            | metric       | what                                                                  |
| ---------------- | ------------ | --------------------------------------------------------------------- |
| Grok Code Fast 1 | 6.7% → 68.3% | Tenfold lift the moment the edit format stops eating the model alive. |
| Gemini 3 Flash   | +5 pp        | Over str_replace — beats Google's own best attempt at the format.     |
| Grok 4 Fast      | −61% tokens  | Output collapses once the retry loop on bad diffs disappears.         |
| MiniMax          | 2.1×         | Pass rate more than doubles. Same weights, same prompt.               |

- `read` : summarized snippets · ideal defaults · selector hit rate
- `search` : fastest in the west
- `lsp` : everything your IDE knows, the agent knows
- `prompts` : adjusted relentlessly for each model

[Read the full post ↗](https://blog.can.ac/2026/02/12/the-harness-problem/)

## The Pi _you love_, with **batteries included**.

Originally built on [Mario Zechner](https://github.com/mariozechner)'s wonderful [Pi](https://github.com/badlogic/pi-mono), 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.

![omp TUI: a single eval session with `[1/2] pandas describe` (Python) printing a real DataFrame.describe() table, followed by `[2/2] top scorer` (JavaScript) running a reduce. Footer: 'Both kernels ran in one session.'](https://omp.sh/captures/eval.webp)

### 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.

![omp TUI: `LSP references` returns five hits across three files for the symbol `formatBytes`, then `LSP rename` applies the change with edits to format.ts/report.ts/cli.ts, then a `Search formatBytes 0 matches` confirmation. Final line: 'Rename complete. Five edits across three files…'.](https://omp.sh/captures/lsp.webp)

### 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.

![omp TUI: a live lldb-dap session against a native binary at /tmp/omp-native/demo. Adapter=lldb-dap, Status=stopped, Frame=xorshift32, Instruction pointer 0x10000055C, Location demo.c:6:10. Debug scopes and Debug variables cards show locals (x = 57351) and the agent confirms the math: x went from 7 → 57351 (= 7 ^ (7<<13)).](https://omp.sh/clips/dap-poster.webp)

_[Watch the capture ↗](https://omp.sh/clips/dap.mp4)_

### 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.

![omp TUI: agent reading src.rs and about to write Box::leak when the request aborts (red `Error: Request was aborted`), an amber `⚠ Injecting rule: box-leak` card injects the rule body `Don't reach for Box::leak in production code paths`, and the agent then course-corrects by proposing `Arc<str>` and asking the user to confirm.](https://omp.sh/clips/ttsr-poster.webp)

_[Watch the capture ↗](https://omp.sh/clips/ttsr.mp4)_

### 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.

![omp TUI showing `task` spawning two subagents `ComponentsExports` and `RoutesExports`, the constraints block requiring an IRC DM between peers, the per-subagent status cards with cost and duration, and a final Findings section listing both exports plus an honest 'IRC coordination note' about a one-sided handshake.](https://omp.sh/clips/irc-poster.webp)

_[Watch the capture ↗](https://omp.sh/clips/irc.mp4)_

### 06 · Read a pdf on arxiv, why not?

web_search chains fourteen ranked providers and hands whatever URLs it finds straight to read. Arxiv PDFs, GitHub pages, Stack Overflow threads come back as structured markdown with anchors intact — the same tool surface you use on local files. Cite, follow, quote, never lose where you came from.

![omp TUI: web_search returns 10 ranked Perplexity sources for inference-time compute scaling, the agent picks an arxiv paper, calls read https://arxiv.org/pdf/2604.10739v1, and summarizes the paper's headline result with real numbers.](https://omp.sh/clips/web-poster.webp)

_[Watch the capture ↗](https://omp.sh/clips/web.mp4)_

### 07 · Unapologetically native. Even on Windows.

Other agents shell out to rg, grep, find, and bash. On many machines those binaries don't exist, and on the ones where they do, every call costs a fork-exec round-trip. omp links the real implementations into the process. ripgrep, glob, find: in-process. brush is the bash, with sessions that survive across calls. The same omp binary runs on macOS, Linux, and Windows — no WSL bridge.

### 08 · Code review with priorities and a verdict

Get a clear verdict on whether the change ships, with every issue ranked P0 through P3 and scored for confidence. /review spawns dedicated reviewer subagents that sweep branches, single commits, or uncommitted work in parallel. You tackle what blocks release first; nothing important hides in a wall of prose.

### 09 · Hashline: edit by content hash

Perfect edits, fewer tokens. The model points at anchors instead of retyping the lines it wants to change, so whitespace battles and string-not-found loops just stop happening. Edit a stale file and the anchors diverge — we reject the patch before it corrupts anything. Grok 4 Fast spends 61% fewer output tokens on the same work.

### 10 · GitHub is just another filesystem

Other harnesses bolt on gh_issue_view, gh_pr_view, gh_search — each with its own parameters the agent has to learn and you have to debug. We skipped that. read already handles paths; PRs are paths. One interface to teach the model, one su