Goose Integration

AVELIN API works seamlessly with Goose — an open-source AI coding agent built by Block (formerly Square). Goose is an extensible, plugin-based agent that can use MCP tools, automate your browser, run terminal commands, and tackle multi-step coding tasks with deep reasoning — all powered by AVELIN's frontier models.

Why AVELIN + Goose? Goose's extensible agent architecture thrives on reliable tool calling and large context windows. AVELIN delivers 1M-token context, ~100 tps throughput, 90% prompt caching discounts, and automatic failover — all through a single OpenAI-compatible endpoint.

What is Goose?

Goose is Block's open-source AI coding agent designed for developers who want a flexible, extensible assistant that goes beyond simple code completion. Its killer feature is a plugin architecture — you can add custom capabilities via MCP (Model Context Protocol) tools, browser automation, terminal access, and more. Built and backed by a publicly traded company, Goose combines enterprise reliability with open-source flexibility.

Goose is ideal for developers who want an agent that can reason across multiple steps, interact with external systems, and be customized to their specific workflow. Whether you're automating repetitive tasks, building integrations, or debugging complex systems, Goose's extensibility lets you shape it to your needs.

Quick Setup

Step 1: Get your AVELIN API key

Sign up at avelin.ai and generate an API key. It will look like sk-ave...xxxx.

Step 2: Install Goose

# macOS / Linux
curl -fsSL https://github.com/block/goose/releases/download/stable/download.sh | bash

# Or via Homebrew
brew install block/tap/goose

# Verify installation
goose --version

Step 3: Configure Goose

Run the interactive configuration wizard:

goose configure

When prompted:

FieldValue
ProviderOpenAI Compatible
Base URLhttps://api.avelin.ai/v1
API Keysk-ave...xxxx
Modelavelin-coding-pro

You can also configure directly via environment variables:

export GOOSE_PROVIDER=openai
export OPENAI_API_BASE=https://api.avelin.ai/v1
export OPENAI_API_KEY=sk-ave...xxxx
export GOOSE_MODEL=avelin-coding-pro

Add these to your ~/.bashrc or ~/.zshrc for persistence.

Step 4: Start Goose

# Start an interactive session
goose run

# Or start with a specific task
goose run "Add error handling to all API endpoints in this project"

Primary Recommendation: avelin-coding-pro

For Goose's agentic workflows:

Featureavelin-coding-proWhy it matters for Goose
Context window1M tokensGoose accumulates context across tool calls, file reads, and terminal output
Max output65K tokensLarge multi-step plans and comprehensive code changes
Throughput~100 tokens/sec2× faster than standard tiers — tighter agent loops
ReasoningDeep step-by-step thinkingBetter multi-step planning and tool orchestration
Tool callingFirst-class supportGoose relies on reliable structured tool calls for MCP, terminal, and browser

Alternative Models

ModelWhen to use
avelin-agentic-proPurpose-built for agentic workflows — best for complex multi-step Goose tasks
avelin-agentic-ultraExtended reasoning for difficult debugging sessions and architecture decisions
avelin-coding-ultraSystem design, large-scale refactors, security reviews
avelin-fastQuick lookups and simple tasks — lowest cost, fastest response

Why AVELIN for Goose?

1. Reliable Tool Calling

Goose fires many tool calls per task — MCP integrations, terminal commands, browser actions, file operations. AVELIN's coding models provide first-class function calling with reliable structured outputs, minimizing retries and malformed calls that break agent loops.

2. Cost Optimization

Goose's agentic loops can consume significant tokens across planning, tool execution, and verification steps. AVELIN optimizes costs:

  • Prompt caching: ~80% cost reduction on repeated system prompts and plugin schemas
  • Competitive pricing: Lower per-token costs than direct provider APIs
  • Pay-per-token: No subscription lock-in — pay only for what you use

3. 1M Context Windows

Goose sessions accumulate context quickly — every tool result, file read, and terminal output adds to the conversation. AVELIN's 1M-token context windows mean longer autonomous sessions without losing track of earlier steps.

4. Automatic Failover

  • Provider failover: If one backend is slow or down, AVELIN switches to another
  • Retry logic: Transient errors are handled automatically
  • 99.9% uptime: Enterprise-grade infrastructure — no interrupted agent sessions

Example Workflow

$ goose run

Goose> I'm ready. What would you like me to help with?

You> Set up a CI/CD pipeline with GitHub Actions for this Node.js project.
     Include linting, testing, and deployment to AWS.

Goose: Let me analyze your project structure first.

[Uses terminal: ls -la, cat package.json, cat tsconfig.json]

I can see this is a Node.js/TypeScript project with Jest tests.
Here's my plan:
1. Create .github/workflows/ci.yml with lint + test jobs
2. Create .github/workflows/deploy.yml with deployment to AWS
3. Add required secrets documentation in DEPLOYMENT.md

Let me build these out...

[Creates .github/workflows/ci.yml]
[Creates .github/workflows/deploy.yml]
[Creates DEPLOYMENT.md]
[Runs: npm run lint — passes]
[Runs: npm test — 42 tests pass]

Done! I've set up:
- CI pipeline: lint → test → build on every PR
- Deploy pipeline: triggered on main branch merge
- Deployment guide with required GitHub secrets

Want me to add anything else?

Enabling Extensions

Goose's power comes from its plugin system. Enable built-in extensions to expand what Goose can do:

# Enable browser automation
goose extension enable browser

# Enable MCP tools
goose extension enable mcp

# List available extensions
goose extension list

Combine Goose extensions with AVELIN's reliable tool calling for powerful automated workflows.

Troubleshooting

IssueSolution
"Provider not supported"Ensure you selected "OpenAI Compatible" as the provider type during goose configure
"Model not found"Verify the model name is exactly avelin-coding-pro (no prefix needed)
"API key invalid"Check that your key starts with sk-ave and the base URL is https://api.avelin.ai/v1
Tool calls failingUse avelin-coding-pro or avelin-agentic-pro — these have first-class function calling
Slow agent loopsTry avelin-agentic-fast for quicker iteration cycles on simple tasks
Context overflowStart a new Goose session or use goose compact to summarize history
MCP extension errorsEnsure your MCP server is running and accessible; check goose extension list