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Developers

Your service, with our governance around it.

Define a tool by hand or import an OpenAPI document. Name, inputs, output, authentication and risk level. It joins the registry and behaves exactly like a built-in capability — permissioned, approvable, rate-limited, audited, revocable.

Narrow beats convenient

One endpoint can become one tool or six. Six narrow tools can each be granted to a different agent and refused to the others; one wide tool cannot be reviewed at all.

Your declared risk level is checked

A tool declared low risk that writes to a ledger is caught in review. Declaring risk is your call; being held to it is ours.

Credentials never reach the agent

Your service's authentication is stored as a secret scoped by agent and environment, and injected at call time. It is never in an agent's context, so it cannot be echoed by a model or read from a log.

Schemas are enforced on the way in

Inputs are validated against your declared schema before your service is called. A malformed call fails at the boundary rather than in your code.

Roughly what it looks like

Illustrative and deliberately short. The reference is at docs.agentlabora.com, and pretending a marketing page is documentation wastes an afternoon.

A tool definition

yaml
name: warehouse.check_stock
description: Stock on hand for one product code.
risk: low
inputs:
  product_code: { type: string, pattern: '^[A-Z]{2}-\d{4}$' }
outputs:
  on_hand: { type: integer }
auth: secret://warehouse-api

Where it stops

The platform governs how your tool is called; it cannot make a badly scoped tool safe. A tool that accepts an arbitrary query string has a risk that depends on what the agent asks for, which means it cannot be meaningfully reviewed — and no amount of permissioning around it fixes that.

Give AI a job.

Build an agent, choose what it can access, define what it may do, and deploy it to work safely across your business.

No code required · Full SDKs and API · Stop any agent instantly · [email protected]