Bonito is an enterprise AI platform designed for multi-cloud workloads, offering multi-provider routing, managed inference, and multi-agent orchestration.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bonito
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install bonito using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Bonito Onboarding?
Bonito streamlines the complexities of modern AI infrastructure by providing a unified gateway for six major providers, including AWS Bedrock, GCP Vertex AI, and Anthropic. This Openclaw Skills integration allows developers to leverage features like automatic cross-provider failover and managed inference, which eliminates the need for individual API keys during the initial setup phase.
The platform is built for scale, supporting everything from simple gateway calls to complex multi-agent systems via Bonobot orchestrators. By using this skill, developers can rapidly onboard onto the Bonito ecosystem, ensuring high availability and cost-effective LLM routing for production-grade AI applications.
Bonito Onboarding Use Cases
- Setting up multi-provider LLM routing with automatic failover to ensure 100% uptime.
- Deploying managed AI agents (BonBon) and complex multi-agent orchestrators (Bonobot).
- Utilizing managed inference to test models without managing multiple provider credentials.
- Integrating Model Context Protocol (MCP) tools and RAG knowledge bases into AI workflows.
- Rapidly prototyping multi-cloud AI workloads using the bonito-cli.
How Bonito Onboarding Works
- User signs up for a Bonito account to access the control plane and API gateway.
- Connectivity is verified via a health check script to ensure the environment can reach the Bonito API.
- The user selects between Managed Inference (no keys needed) or connecting their own provider keys (e.g., Groq, OpenAI).
- A Gateway API Key is generated to route requests through Bonito's intelligent failover layer.
- AI agents are defined and deployed using the CLI or YAML configurations, specifying models and system prompts.
- Advanced orchestration is triggered for multi-agent fan-out, delegating tasks across different specialized agents.
Bonito Onboarding Setup
To begin using this skill for Openclaw Skills, install the official CLI and authenticate your environment:
# Install the Bonito CLI
pip install bonito-cli
# Authenticate with your Bonito account
bonito auth login
# Verify your local deployment environment
python3 scripts/verify_deploy.py
Bonito Onboarding Data Schema & Taxonomy
Bonito organizes its architecture through a hierarchical taxonomy defined in the bonito.yaml configuration file:
| Component | Description |
|---|---|
| Providers | Credentials and routing settings for LLM backends (AWS, Azure, etc.). |
| Knowledge Bases | Vector stores and RAG data sources for agent context. |
| BonBon Agents | Individual specialized workers with specific system prompts and models. |
| Bonobot | High-level orchestrators that manage multi-agent delegation. |
| Gateway Keys | Authentication tokens used to route traffic through the unified API endpoint. |
Bonito Onboarding Advanced Features
- Cross-provider failover: Automatically reroutes traffic to secondary providers if a primary LLM (e.g., Anthropic) experiences downtime.
- Bonobot Orchestration: Supports complex multi-agent fan-out and task delegation.
- MCP Tool Integration: Connects agents to external tools and data sources via the Model Context Protocol.
- Environment Variable Injection: Supports
${ENV_VAR:-default}syntax withinbonito.yamlfor flexible multi-stage deployments. - Managed Inference: Accelerated onboarding path that allows immediate testing of Llama 3 and other models without individual provider billing.
SKILL.md
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