oh-my-pi
⌥ Coding agent with the IDE wired in. Built by Stencil Labs.
Install / Use
claude mcp add can1357 -- npx -y github:can1357/oh-my-piIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of oh-my-pi
oh-my-pi scores 87/100 on our quality scale, 471st of 965 AI & Machine Learning skills we index (top 49%).
Its MCP Server is 43 KB long, well organised into 61 sections with 16 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.
With 37,945 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated today, so oh-my-pi is actively maintained.
- Our last check on 2026-10-20 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 95/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (2 minor notes below). An AI review of the same text found nothing harmful.
- noteInstalls by piping a downloaded script into a shellline 40
curl -fsSL https://omp.sh/install | sh - noteInstalls by piping a downloaded script into a shellline 85
irm https://omp.sh/install.ps1 | iex
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
oh-my-pi compared with similar skills
All 4 of these similar skills score higher than oh-my-pi; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| oh-my-pi (this skill)by can1357 | 87 | 37.9k | today | MCP Server |
| claude-memby thedotmack | 100 | 113.5k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.2k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 90.9k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.9k | today | CLAUDE.md |
Frequently asked questions
- How do I install oh-my-pi?
- Run
claude mcp add can1357 -- npx -y github:can1357/oh-my-pi. The install tabs above show the steps for each supported agent. - Which AI agents does oh-my-pi work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is oh-my-pi safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (2 minor notes below). An AI review of the same text found nothing harmful. It is MIT-licensed and scores 95/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is oh-my-pi still maintained?
- The repository was last updated today, so oh-my-pi is actively maintained.
Skill content
View source on GitHubThe 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
Alpine / musl: the prebuilt musl binary links
libstdc++/libgccdynamically, 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 profile install github:can1357/oh-my-pi
Flake consumers can use packages.<system>.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.
| 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 rategrep: fastest in the westlsp: everything your IDE knows, the agent knowsprompts: adjusted relentlessly for each model
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.
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.
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.
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 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.
07 · Hand someone the link, they're in.
/collab puts your live session on a relay and hands back a link — and a QR. A teammate joins from another terminal with omp join, or just opens it in a browser. Share read-write to pair on the same agent, or /collab view for a read-only link anyone can watch but no one can steer. Frames are sealed client-side; the relay never sees your keys.
08 · Read a pdf on arxiv, why not?
web_search chains twenty-three 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.
09 · 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, and 58 command-line utilities (ls, sed, sort, xargs, even jq) ported into the builtins crate and run in-process, zero fork/exec. The same omp binary runs on macOS, Linux, and Windows — no WSL bridge.
10 · 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.
Want to steer the review yourself? /annotate code-review opens the diff so you can pin notes to lines bef
Truncated for display — read the full file on GitHub.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.