oh-my-pi

AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI libraries

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oh-my-pi is an AI coding agent for the terminal, providing tools for interactive coding, AI-powered git commits, Python code execution, LSP integration, time-traveling streamed rules, interactive code review, task management, interactive questioning, custom TypeScript slash commands, universal config discovery, MCP & plugin system, web search & fetch, SSH tool, Cursor provider integration, multi-credential support, image generation, TUI overhaul, edit fuzzy matching, and more. It offers a modern terminal interface with smart session management, supports multiple AI providers, and includes various tools for coding, task management, code review, and interactive questioning.

README:

AI coding agent for the terminal

Fork of badlogic/pi-mono by @mariozechner

Installation

Via Bun (recommended)

Requires Bun runtime:

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

Via installer script

Linux / macOS:

curl -fsSL https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.sh | sh

Windows (PowerShell):

irm https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.ps1 | iex

By default, the installer uses bun if available, otherwise downloads the prebuilt binary.

Options:

--source / -Source: Install via bun (installs bun first if needed)
--binary / -Binary: Always use prebuilt binary
--ref <ref> / -Ref <ref>: Install a tag/commit/branch (defaults to source install)

# Force bun installation
curl -fsSL .../install.sh | sh -s -- --source

# Install a tag via binary
curl -fsSL .../install.sh | sh -s -- --binary --ref v3.20.1

# Install a branch or commit via source
curl -fsSL .../install.sh | sh -s -- --source --ref main

# Install a tag via binary
& ([scriptblock]::Create((irm https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.ps1))) -Binary -Ref v3.20.1

# Install a branch or commit via source
& ([scriptblock]::Create((irm https://raw.githubusercontent.com/can1357/oh-my-pi/main/scripts/install.ps1))) -Source -Ref main

Manual download

Download binaries directly from GitHub Releases.

+ Commit Tool (AI-Powered Git Commits)

AI-powered conventional commit generation with intelligent change analysis:

Agentic mode: Tool-based git inspection with git-overview, git-file-diff, git-hunk for fine-grained analysis
Split commits: Automatically separates unrelated changes into atomic commits with dependency ordering
Hunk-level staging: Stage individual hunks when changes span multiple concerns
Changelog generation: Proposes and applies changelog entries to CHANGELOG.md files
Commit validation: Detects filler words, meta phrases, and enforces conventional commit format
Legacy mode: --legacy flag for deterministic pipeline when preferred
Run via omp commit with options: --push, --dry-run, --no-changelog, --context

+ Python Tool (IPython Kernel)

Execute Python code with a persistent IPython kernel and 30+ shell-like helpers:

Streaming output: Real-time stdout/stderr with image and JSON rendering
Prelude helpers: cat(), sed(), rsed(), find(), grep(), batch(), sh(), run() and more
Git utilities: git_status(), git_diff(), git_log(), git_show() for repository operations
Line operations: extract_lines(), delete_lines(), insert_lines(), lines_matching() for text manipulation
Shared gateway: Resource-efficient kernel reuse across sessions (python.sharedGateway setting)
Custom modules: Load extensions from .omp/modules/ and .pi/modules/ directories
Rich output: Supports display() for HTML, Markdown, images, and interactive JSON trees
Mermaid diagrams: Renders mermaid code blocks as inline graphics in iTerm2/Kitty terminals
Install dependencies via omp setup python

+ LSP Integration (Language Server Protocol)

Full IDE-like code intelligence with automatic formatting and diagnostics:

Format-on-write: Auto-format code using the language server's formatter (rustfmt, gofmt, prettier, etc.)
Diagnostics on write/edit: Immediate feedback on syntax errors and type issues after every file change
Workspace diagnostics: Check entire project for errors (lsp action=workspace_diagnostics)
40+ language configs: Out-of-the-box support for Rust, Go, Python, TypeScript, Java, Kotlin, Scala, Haskell, OCaml, Elixir, Ruby, PHP, C#, Lua, Nix, and many more
Local binary resolution: Auto-discovers project-local LSP servers in node_modules/.bin/, .venv/bin/, etc.
Hover docs, symbol references, code actions, workspace-wide symbol search

+ Time Traveling Streamed Rules (TTSR)

Zero context-use rules that inject themselves only when needed:

Pattern-triggered injection: Rules define regex triggers that watch the model's output stream
Just-in-time activation: When a pattern matches, the stream aborts, the rule injects as a system reminder, and the request retries
Zero upfront cost: TTSR rules consume no context until they're actually relevant
One-shot per session: Each rule only triggers once, preventing loops
Define via ttsrTrigger field in rule files (regex pattern)

Example: A "don't use deprecated API" rule only activates when the model starts writing deprecated code, saving context for sessions that never touch that API.

+ Interactive Code Review

Structured code review with priority-based findings:

/review command: Interactive mode selection (branch comparison, uncommitted changes, commit review)
Structured findings: report_finding tool with priority levels (P0-P3: critical → nit)
Verdict rendering: aggregates findings into approve/request-changes/comment
Combined result tree showing verdict and all findings

+ Task Tool (Subagent System)

Parallel execution framework with specialized agents and real-time streaming:

5 bundled agents: explore, plan, browser, task, reviewer
Parallel exploration: Reviewer agent can spawn explore agents for large codebase analysis
Real-time artifact streaming: Task outputs stream as they're created, not just at completion
Output tool: Read full agent outputs by ID when truncated previews aren't sufficient
Isolated execution: isolated: true runs tasks in git worktrees, generates patches, and applies cleanly
User-level (~/.omp/agent/agents/) and project-level (.omp/agents/) custom agents
Concurrency-limited batch execution with progress tracking

+ Model Roles

Configure different models for different purposes with automatic discovery:

Three roles: default (main model), smol (fast/cheap), slow (comprehensive reasoning)
Auto-discovery: Smol finds haiku → flash → mini; Slow finds codex → gpt → opus → pro
Role-based selection: Task tool agents can use model: pi/smol for cost-effective exploration
CLI args (--smol, --slow) and env vars (PI_SMOL_MODEL, PI_SLOW_MODEL)
Configure via /model selector with keybindings (Enter=default, S=smol, L=slow)

+ Todo Tool (Task Tracking)

Structured task management with persistent visual tracking:

todo_write tool: Create and manage task lists during coding sessions
Persistent panel: Todo list displays above the editor with real-time progress
Task states: pending, in_progress, completed with automatic status updates
Completion reminders: Agent warned when stopping with incomplete todos (todoCompletion setting)
Toggle visibility: Ctrl+T expands/collapses the todo panel

+ Ask Tool (Interactive Questioning)

Structured user interaction with typed options:

Multiple choice questions: Present options with descriptions for user selection
Multi-select support: Allow multiple answers when choices aren't mutually exclusive
Multi-part questions: Ask multiple related questions in sequence via questions array parameter

+ Custom TypeScript Slash Commands

Programmable commands with full API access:

Create at ~/.omp/agent/commands/[name]/index.ts or .omp/commands/[name]/index.ts
Export factory returning { name, description, execute(args, ctx) }
Full access to HookCommandContext for UI dialogs, session control, shell execution
Return string to send as LLM prompt, or void for fire-and-forget actions
Also loads from Claude Code directories (~/.claude/commands/, .claude/commands/)

+ Universal Config Discovery

Unified capability-based discovery that loads configuration from 8 AI coding tools:

Multi-tool support: Claude Code, Cursor, Windsurf, Gemini, Codex, Cline, GitHub Copilot, VS Code
Discovers everything: MCP servers, rules, skills, hooks, tools, slash commands, prompts, context files
Native format support: Cursor MDC frontmatter, Windsurf rules, Cline .clinerules, Copilot applyTo globs, Gemini system.md, Codex AGENTS.md
Provider attribution: See which tool contributed each configuration item
Discovery settings: Enable/disable individual providers via /config interactive tab
Priority ordering: Multi-path resolution across .omp, .pi, and .claude directories

+ MCP & Plugin System

Full Model Context Protocol support with external tool integration:

Stdio and HTTP transports for connecting to MCP servers
Plugin CLI (omp plugin install/enable/configure/doctor)
Hot-loadable plugins from ~/.omp/plugins/ with npm/bun integration
Automatic Exa MCP server filtering with API key extraction

+ Web Search & Fetch

Multi-provider search and full-page scraping with 80+ specialized scrapers:

Multi-provider search: Anthropic, Perplexity, and Exa with automatic fallback chain
80+ site-specific scrapers: GitHub, GitLab, npm, PyPI, crates.io, arXiv, PubMed, Stack Overflow, Hacker News, Reddit, Wikipedia, YouTube transcripts, and many more
Package registries: npm, PyPI, crates.io, Hex, Hackage, NuGet, Maven, RubyGems, Packagist, pub.dev, Go packages
Security databases: NVD, OSV, CISA KEV vulnerability data
HTML-to-markdown conversion with link preservation

+ SSH Tool

Remote command execution with persistent connections:

Project discovery: Reads SSH hosts from ssh.json / .ssh.json in your project
Persistent connections: Reuses SSH connections across commands for faster execution
OS/shell detection: Automatically detects remote OS and shell type
SSHFS mounts: Optional automatic mounting of remote directories
Compat mode: Windows host support with automatic shell probing

+ Cursor Provider

Use your Cursor Pro subscription for AI completions:

Browser-based OAuth: Authenticate through Cursor's OAuth flow
Tool execution bridge: Maps Cursor's native tools to omp equivalents (read, write, shell, diagnostics)
Conversation caching: Persists context across requests in the same session
Shell streaming: Real-time stdout/stderr during command execution

+ Multi-Credential Support

Distribute load across multiple API keys:

Round-robin distribution: Automatically cycles through credentials per session
Usage-aware selection: For OpenAI Codex, checks account limits before credential selection
Automatic fallback: Switches credentials mid-session when rate limits are hit
Consistent hashing: FNV-1a hashing ensures stable credential assignment per session

+ Image Generation

Create images directly from the agent:

Gemini integration: Uses gemini-3-pro-image-preview by default
OpenRouter fallback: Automatically uses OpenRouter when OPENROUTER_API_KEY is set
Inline display: Images render in terminals supporting Kitty/iTerm2 graphics
Saves to temp files and reports paths for further manipulation

+ TUI Overhaul

Modern terminal interface with smart session management:

Auto session titles: Sessions automatically titled based on first message using smol model
Welcome screen: Logo, tips, recent sessions with selection
Powerline footer: Model, cwd, git branch/status, token usage, context %
LSP status: Shows which language servers are active and ready
Hotkeys: ? displays shortcuts when editor empty
Persistent prompt history: SQLite-backed with Ctrl+R search across sessions
Grouped tool display: Consecutive Read calls shown in compact tree view
Emergency terminal restore: Crash handlers prevent terminal corruption

+ Edit Fuzzy Matching

Handles whitespace and indentation variance automatically:

High-confidence fuzzy matching for oldText in edit operations
Fixes the #1 pain point: edits failing due to invisible whitespace differences
Configurable via edit.fuzzyMatch setting (enabled by default)

... and many more

omp config subcommand: Manage settings from CLI (list, get, set, reset, path)
omp setup subcommand: Install optional dependencies (e.g., omp setup python for Jupyter kernel)
omp stats subcommand: Local observability dashboard for AI usage (requests, cost, cache rate, tokens/s)
xhigh thinking level: Extended reasoning for Anthropic models with increased token budgets
Background mode: /background detaches UI and continues agent execution
Completion notifications: Configurable bell/OSC99/OSC9 when agent finishes
65+ built-in themes: Catppuccin, Dracula, Nord, Gruvbox, Tokyo Night, and material variants
Auto environment detection: OS, distro, kernel, CPU, GPU, shell, terminal, DE in system prompt
Git context: System prompt includes branch, status, recent commits
Bun runtime: Native TypeScript execution, faster startup, all packages migrated
Centralized file logging: Debug logs with daily rotation to ~/.omp/logs/
Bash interceptor: Optionally block shell commands that have dedicated tools
@file auto-read: Type @path/to/file in prompts to inject file contents inline
Additional tools: AST (structural code analysis), Replace (find & replace across files)

Packages

Package	Description
@oh-my-pi/pi-ai	Multi-provider LLM client (Anthropic, OpenAI, Gemini, Bedrock, Cursor, Codex, Copilot)
@oh-my-pi/pi-agent-core	Agent runtime with tool calling and state management
@oh-my-pi/pi-coding-agent	Interactive coding agent CLI
@oh-my-pi/pi-tui	Terminal UI library with differential rendering
@oh-my-pi/pi-natives	WASM bindings for native text, image, and grep operations
@oh-my-pi/omp-stats	Local observability dashboard for AI usage statistics

Rust Crates

Crate	Description
pi-natives	Rust N-API crate for performance-critical ops

License

MIT - Original work copyright Mario Zechner

For Tasks:

Click tags to check more tools for each tasks

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software developer ai engineer data scientist devops engineer system administrator

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