Getting Started

Quick Start

Get up and running with cora in three simple steps.

1. Install cora — Single binary, no runtime dependencies: curl -fsSL https://raw.githubusercontent.com/codecoradev/cora-cli/main/install.sh | sh

2. Authenticate — Run cora auth login to pick your provider and enter your API key. Cora stores the API key in ~/.cora/auth.toml (never committed to git) and provider settings in ~/.cora/config.yaml.

3. Review — Analyze your staged changes: cora review

Authentication — cora auth login

The interactive login guides you through provider selection:

$ cora auth login

🔑 Cora Auth Setup
   Choose your LLM provider:

  [1] openai
  [2] anthropic
  [3] groq
  [4] ollama
  [5] zai
  [6] custom

  Select provider [1-6]: 5

  → Provider: zai
  🔑 Found ZAI_API_KEY in environment
     Use it? [Y/n]: Y
     ✅ Using ZAI_API_KEY from environment

  Model [glm-5.1]:          ← press Enter to accept default
  Base URL [https://api.z.ai/api/coding/paas/v4]:  ← press Enter to accept default

✅ API key saved to ~/.cora/auth.toml
   Provider: zai | Model: glm-5.1 | Base: https://api.z.ai/api/coding/paas/v4

Term	Description
Known providers	Provider env vars auto-detected (e.g. ZAI_API_KEY)
Custom provider	Enter your own base URL, model name, and API key
API key	Saved to ~/.cora/auth.toml (secret)
Provider settings	Saved to ~/.cora/config.yaml

Check your auth status anytime:

$ cora auth status
✅ API key is configured.
   Source: ~/.cora/auth.toml

   Provider: openai
   Model: gpt-4o-mini
   Base URL: https://api.openai.com/v1

You can also use provider environment variables: OPENAI_API_KEY, ANTHROPIC_API_KEY, ZAI_API_KEY, etc. CORA_API_KEY is reserved for CI use.

Understanding the Output

cora outputs a structured, color-coded summary of findings for each file reviewed.

$ cora review --staged

Analyzing 3 files...
✓ src/auth/login.ts — 2 issues found
  ⚠ Line 42: Potential SQL injection
  ⚠ Line 87: Hardcoded secret
✓ src/utils/parser.ts — clean
✓ src/api/routes.ts — 1 issue found
  ✗ Line 23: Missing error handling

3 issues found in 3 files

Each line in the output contains:

Term	Description
file path	The relative path to the file being reviewed
line number	Specific line where the issue was found
severity	Suggestion (⚠), Warning (⚠), or Error (✗)
description	Brief explanation of the issue

Project Configuration — cora init

Create a .cora.yaml config file in your project root. Automatically installs a pre-commit hook that runs cora review --staged --format compact before each commit. Use --no-hook to skip hook installation.

$ cora init
✅ Created .cora.yaml with example configuration.
✅ Pre-commit hook installed at .git/hooks/pre-commit

Set provider, model, and base URL directly in .cora.yaml (no nested section needed):

# .cora.yaml — shortcut format
provider: openai
model: gpt-4o-mini
base_url: https://api.openai.com/v1

Key configuration options:

Key	Description
focus	Review focus areas: security, performance, bugs, best_practice
ignore	File patterns and rules to skip
hook	Pre-commit hook settings: mode, severity threshold, max diff size
llm	LLM parameters: temperature, max_tokens, timeout

Next Steps

Now that you have cora running, explore these topics to get the most out of it:

• Installation — install options and shell completions
• Usage — review modes, output formats, and configuration
• Configuration — full .cora.yaml reference, quality gate, security scanner, MCP server
• Providers — setting up OpenAI, Anthropic, Groq, Ollama, and Z.AI
• CLI Reference — full command documentation
• Examples — CI/CD setup for GitHub, GitLab, Gitea, Bitbucket

Daily Workflow

Once set up, your daily workflow becomes:

git add -A
cora commit          # review + generate commit message + commit

Or skip the prompt in CI/trusted workflows:

cora commit --yolo    # auto-commit, no prompts

Memory-Powered Reviews (Optional)

Install Uteke to give Cora a memory:

# Install both tools
curl -fsSL https://raw.githubusercontent.com/codecoradev/cora-cli/main/install-bundle.sh | sh

Then enable memory in reviews:

cora review --staged --memory         # recall project patterns
cora review --staged --memory --learn # recall + save findings

• --memory — Cora recalls past review findings and code patterns from Uteke before reviewing
• --learn — After review, Cora saves findings to Uteke for future recall
• Works with any review mode (staged, unpushed, branch)

Your code review gets smarter every sprint.

AI Agent Integration

cora includes a built-in MCP server for AI coding agents. After installation:

# Start MCP server
$ cora mcp

Configure in Claude Code (.claude/settings.json) or Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "cora": {
      "command": "cora",
      "args": ["mcp"]
    }
  }
}

See Configuration → MCP Server for full setup guides.