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