revcli

LLM-powered code reviewer CLI.

revcli is a local command-line tool that acts as an intelligent peer reviewer. It reads your local git changes and uses your chosen LLM provider to analyze your code for bugs, optimization opportunities, and best practices—all before you push a single commit.

Features

Smart Context: Analyzes git diff plus full file contents to understand exactly what you changed and where it fits.
Branch Comparison: Compare against any branch or commit with --base flag (perfect for MR/PR reviews).
Context Preview: See exactly which files and how many tokens will be sent before the review.
Token Usage Display: Track actual token usage after each review.
Privacy-First: Runs locally with built-in secret detection to prevent accidentally sending credentials to the LLM.
Interactive Chat: Ask follow-up questions about the review in an interactive TUI.
Multi-Provider: Use cloud APIs (Gemini, Claude, GPT, etc.) or local LLMs (Ollama, LM Studio, vLLM) via a single config.

Supported providers

revcli supports many LLM providers. The list is supplied by Catwalk (Charm’s provider registry) and can be updated with revcli update-providers. Supported provider types include:

| Type | Description | |------|-------------| | Google (Gemini) | Google AI Studio – e.g. gemini-3.0-pro, gemini-3.0-flash | | Google Vertex AI | Google Cloud Vertex AI | | OpenAI | OpenAI API – e.g. gpt-5.4, gpt-5.4-mini | | Anthropic | Claude models – e.g. claude-opus-4.6, claude-sonnet-4-6 | | Azure OpenAI | Azure-hosted OpenAI-compatible endpoints | | AWS Bedrock | Amazon Bedrock (e.g. Claude on Bedrock) | | OpenRouter | OpenRouter – many models behind one API | | OpenAI-compatible (local) | Any server that speaks the OpenAI API: Ollama, LM Studio, vLLM, LocalAI, etc. |

You choose a provider and model in ~/.config/revcli/config.yaml or via the TUI when you run revcli without arguments. Code review uses your configured large model.

Prerequisites

Before using the tool, ensure you have the following installed:

Go (version 1.25 or higher)
Git installed and initialized in your project.
At least one LLM provider configured (API key or local endpoint). Examples:
- Google Gemini: Get an API key here.
- OpenAI: API key from platform.openai.com.
- Anthropic: API key from console.anthropic.com.
- Local (Ollama, LM Studio, etc.): No key needed; set base_url in config (e.g. http://localhost:11434/v1 for Ollama).

Installation

You can install the tool directly using go install:

go install github.com/trankhanh040147/revcli@latest

Or build from source:

git clone https://github.com/trankhanh040147/revcli.git
cd revcli
make build

Then run revcli to start the interactive TUI (see Usage below).

Configuration

Configure your provider(s) in ~/.config/revcli/config.yaml. The app can also prompt you to pick a provider and model when you run revcli (no args).

Cloud providers: Set the provider’s API key in the config or via the relevant env var (e.g. GEMINI_API_KEY, OPENAI_API_KEY, ANTHROPIC_API_KEY). Keys are not overridable via a review command flag; use the config or env.
Local LLMs (Ollama, LM Studio, vLLM, etc.): Add a provider with type: openai-compat and base_url pointing to your server (e.g. http://localhost:11434/v1 for Ollama). No API key required for most local setups.

To refresh the list of available providers and models from the Catwalk registry:

revcli update-providers

Usage

Getting started — run revcli

The main way to use revcli is to run:

revcli

This launches the interactive TUI: you choose a provider and model (or set one up if needed), then you can start a code review or chat with the AI from the same interface. Use this when you want the full experience (sessions, follow-up chat, file list, presets).

To review code directly from the command line (e.g. in scripts or CI), use revcli review instead (see below).

Basic Review

Review all uncommitted changes in your repository:

revcli review

Review Against a Branch (MR/PR Style)

Compare your current changes against a base branch - perfect for merge request reviews:

# Compare against main branch
revcli review --base main

# Compare against develop branch
revcli review --base develop

# Compare against a specific commit
revcli review --base abc1234

Review Staged Changes Only

Review only the changes you've staged for commit:

revcli review --staged

Use a Specific Model

The model used for review is your configured large model in ~/.config/revcli. You can change it via the TUI (run revcli and pick a provider/model) or by editing the config. The --model flag lets you request a specific model name for the current provider:

revcli review --model gemini-3.0-flash

Non-Interactive Mode

Get the review output without the interactive chat interface:

revcli review --no-interactive

Skip Secret Detection

If you're confident there are no secrets in your code (use with caution):

revcli review --force

Use Review Presets

Apply predefined review styles for focused analysis:

# Quick, high-level review
revcli review --preset quick

# Comprehensive, detailed review
revcli review --preset strict

# Security-focused review
revcli review --preset security

# Performance optimization focus
revcli review --preset performance

Available presets: quick, strict, security, performance, logic, style, typo, naming

You can also create custom presets in ~/.config/revcli/presets/*.yaml. See Development Roadmap for details.

Manage Presets

Manage your custom presets with dedicated commands:

# List all presets (built-in and custom)
revcli preset list

# Create a new custom preset
revcli preset create my-preset

# Show preset details
revcli preset show my-preset

# Delete a custom preset
revcli preset delete my-preset

Interactive Mode

When running in interactive mode (default), you can:

View the review: The AI analysis is displayed in a scrollable viewport
Ask follow-up questions: Press Enter to enter chat mode, then Alt+Enter to send
Navigate: Use Vim-style keys (j/k for up/down, g/G for top/bottom) or arrow keys; half/full page: Ctrl+d / Ctrl+u, Ctrl+f / Ctrl+b
Search: Press / to search within the review, n/N for next/previous match, Tab to toggle highlight/filter mode, Esc to exit search
File list: Press i to enter file list (prune files from context), j/k to navigate, Enter to view selected file, Esc to back to review
Yank to clipboard: Press y (or yy) to copy entire review, Y for last response only
Prompt history: In chat mode, use Ctrl+P (previous) and Ctrl+N (next) to navigate prompt history
Web search: In chat, press Ctrl+W to toggle web search for the model
Cancel requests: Press Ctrl+X to cancel a streaming request
Help: Press ? to see all available keybindings
Exit: Press q to quit, Esc to exit chat mode

See the help overlay for the complete list of keyboard shortcuts.

Context Preview

Before sending to the API, revcli shows you exactly what will be reviewed:

📋 Review Context
─────────────────

📁 Files to review:
   • internal/api/handler.go (2.3 KB)
   • internal/api/middleware.go (1.1 KB)
   • cmd/server.go (856 B)

   Total: 3 files, 4.3 KB

🚫 Ignored files:
   • go.sum
   • internal/api/handler_test.go

📊 Token Estimate: ~1,250 tokens

Token Usage

After each review, you'll see the actual token usage:

✓ Review completed in 3.2s
📊 Token Usage: 1,247 prompt + 892 completion = 2,139 total

What Gets Reviewed

The tool analyzes:

All modified source files
The git diff showing exact changes
Full file context for better understanding

The tool automatically filters out:

go.sum and go.mod files
vendor/ directory
Generated files (*_generated.go, *.pb.go)
Test files (*_test.go)
Mock files

Security

The tool includes basic secret detection that scans for:

API keys and tokens
Passwords and secrets
Private keys
Database URLs with credentials
Common credential patterns

If potential secrets are detected, the review is aborted unless --force is used.

Review Focus Areas

The AI reviewer acts as a Senior Engineer and focuses on:

Bug Detection - Logic errors, nil pointer dereferences, race conditions
Idiomatic Patterns - Best practices for your language
Performance Optimizations - Unnecessary allocations, inefficient loops
Security Concerns - Input validation, injection risks
Code Quality - Readability, documentation, test coverage suggestions

Example Output

🔍 Code Review

📋 Review Context
─────────────────
📁 Fil

Revcli

Install / Use

README