Architecture at a glance

AgentsKit works best when you think of it as a layered ecosystem, not a single framework.

At the center is a small contract layer. Around it are packages for UI, runtime, data, and production. You can start with one layer and add the rest as your agent becomes more capable.

The stack in one view

graph TD
    core["@agentskit/core\ncontracts + primitives"]

    ui["@agentskit/react · @agentskit/ink · framework bindings\nchat surfaces"]
    providers["@agentskit/adapters\nmodel providers"]
    runtime["@agentskit/runtime\nloops, delegation, orchestration"]
    capabilities["@agentskit/tools · @agentskit/skills\nactions + behavior"]
    data["@agentskit/memory · @agentskit/rag\ncontext + retrieval"]
    ops["@agentskit/observability · @agentskit/eval · @agentskit/sandbox\ntrust + production controls"]
    cli["@agentskit/cli · @agentskit/templates\nbootstrap + workflows"]

    core --> ui
    core --> providers
    core --> runtime
    core --> capabilities
    core --> data
    core --> ops
    core --> cli

    providers --> runtime
    capabilities --> runtime
    data --> runtime
    runtime --> ui
    ops --> runtime
    cli --> ui
    cli --> runtime

What each layer does

The six contracts

The reason the ecosystem composes is that the layers meet through six stable contracts:

• Adapter — swap model providers
• Tool — expose actions to the model
• Skill — package behavior and prompts
• Memory — persist and reload context
• Retriever — fetch external context
• Runtime — compose the loop that ties everything together

Deep dive: Concepts

Three common adoption paths

1. UI first

Start with @agentskit/react or @agentskit/ink, then add runtime and tools once the chat needs to do real work.

Best for:

• chat products
• prototypes
• customer-facing assistants

2. Runtime first

Start with @agentskit/runtime and @agentskit/tools, then add a UI later if the workflow proves useful.

Best for:

• jobs
• internal automations
• research agents
• coding agents

3. Knowledge first

Start with @agentskit/rag, @agentskit/memory, and a UI or runtime entry point, then harden with production controls.

Best for:

• internal copilots
• support assistants
• retrieval-heavy apps

How teams usually grow the stack

1. Pick a provider and a single entry point.
2. Add runtime when the task becomes multi-step.
3. Add tools when the model needs to act.
4. Add memory and retrieval when context needs to persist.
5. Add observability, evals, and safety before wider rollout.

Where to go next

• Build your first agent
• Use cases
• Packages overview
• agentskit init