AGK - AgenticGoKit CLI

The Unified Toolchain for Agentic AI Systems

AGK is the official CLI for AgenticGoKit, designed to manage the entire lifecycle of intelligent agents. From scaffolding new projects to distributing templates and observing production workflows, AGK provides a standardized interface for building the next generation of AI software.

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Vision: The Complete Lifecycle

AGK aims to streamline the developer experience across five key pillars:

1. Create: Scaffold powerful agents instantly using a rich registry of templates.
2. Test: Validate workflows with semantic matching and automated evaluation.
3. Observe: Gain deep observability into your agent's reasoning, prompts, and performance.
4. Distribute: (Planned) Share your agent architectures and workflows with the community or your team.
5. Deploy: (Planned) Seamlessly ship agents to cloud platforms, Kubernetes, or edge devices.

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Quick Start

1. Installation

# Build from source
cd agk
go build -o agk main.go

2. Create Your First Agent

# Initialize a new project with the quickstart template
./agk init my-agent --template quickstart --llm openai

# Navigate to the project
cd my-agent

# Install dependencies
go mod tidy

3. Run It

# Set your API key
export OPENAI_API_KEY=sk-...

# Run the agent
go run main.go

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Templates & Registry

AGK features a powerful template system that lets you use both built-in and community-created templates. Explore the Official Template Registry.

Use a Template

./agk init enterprise-bot --template workflow --llm anthropic

Manage Templates

Bring in templates from GitHub, local folders, or other sources.

# List all available templates (built-in + cached)
agk template list

# Add a template from a remote source
agk template add github.com/username/my-template

# Remove a cached template
agk template remove my-template

Want to build your own? Check out the Creating Templates Guide.

Built-in Templates

Template	Best For	Description
Quickstart	Learning	Minimal setup. Single file. Hardcoded config. Perfect for understanding the basics.
Workflow	Pipelines	Multi-step workflow (e.g. Sequential, Parallel) structure.

Run agk init --list to see all available templates including those from the registry.

Example usage:

./agk init enterprise-bot --template workflow --llm anthropic

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🧪 Eval - Automated Testing

AGK provides a comprehensive evaluation framework for testing AI workflows with semantic matching, confidence scoring, and professional reports.

Features

• Semantic Matching: Embedding similarity, LLM-as-judge, or hybrid strategies
• Confidence Scoring: Quantify how well outputs match expectations (0.0 - 1.0)
• Professional Reports: Auto-generated markdown with collapsible sections and visualizations
• EvalServer Integration: HTTP server mode for automated testing
• Multiple Strategies: Choose the right evaluation approach for your use case

Quick Example

# semantic-tests.yaml
name: "My Workflow Tests"
description: "Evaluate AI workflow outputs"

evalserver:
  url: "http://localhost:8787"
  workflow_name: "story"
  timeout: "180s"

semantic:
  strategy: "llm-judge"  # or "embedding" or "hybrid"
  threshold: 0.70
  llm:
    provider: "ollama"
    model: "llama3.2"

tests:
  - name: "Generate Report Test"
    input: "artificial intelligence"
    expected_output: |
      A comprehensive technical report with structured sections

# Run evaluations
agk eval semantic-tests.yaml --timeout 200

# View report
cat .agk/reports/eval-report-*.md

Learn more: See Eval Documentation for detailed guides on strategies, configuration, and best practices.

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🔍 Trace - Observability

AGK includes a powerful Trace system to help you understand exactly what your agents are thinking.

1. Capture Traces

Control data granularity with AGK_TRACE_LEVEL:

Level	Data Captured	Use Case
minimal	Timing, status	Production monitoring
standard	+ Tokens, latency	General debugging
detailed	+ Prompts, responses, tool args	Deep evaluation & auditing

# Enable detailed tracing to see prompts and thoughts
$env:AGK_TRACE="true"
$env:AGK_TRACE_LEVEL="detailed"
go run main.go

2. Analyze Traces

Interactive Viewer (TUI) Browse traces, explore spans, and view content details.

agk trace view
# Tip: Press 'd' on a span to see the full Prompt & Response content!

List & Show Quick access to trace summaries.

agk trace list
agk trace show <trace-id>

Visual Flowchart (Mermaid) Generate a diagram of the agent's execution path.

agk trace mermaid > trace_flow.md

Learn more: See Trace Documentation for advanced usage and debugging workflows.

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🛠️ Commands

Command	Description
init	Create a new project from a template.
init --list	Show details of all available templates.
eval	Run automated tests against workflows with semantic matching.
trace list	List all captured trace runs.
trace show	Display summary of a specific run.
trace view	Open the interactive TUI trace explorer.
trace mermaid	Generate Mermaid flowchart of trace execution.

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Roadmap

Completed

• Template Registry System (list, add, remove)
• Smart Scaffolding (Quickstart, Workflow bases)
• Eval Framework (Semantic matching, LLM-as-judge, professional reports)
• Trace System (Interactive TUI, Mermaid export, detailed spans)
• Streaming Support (Native across all templates)

In Progress

• Multi-Agent Templates
• Advanced Full-Stack Templates

Planned

• Template Distribution (pack, push)
• Cloud Deployment Engine (agk deploy)
• Workflow Visualization (Interactive graph editor)
• Interactive Init Wizard (agk init -i)
• MCP Server Management
• RAG & Knowledge Base Management

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🤝 Contributing

We love contributions! Please read CONTRIBUTING.md for guidelines.

� License

Apache 2.0 - See LICENSE.

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