Create an agent
Turn a well-defined job into a reusable AI worker.
An effective agent starts with a narrow responsibility and a result you can evaluate. Avoid creating a universal assistant with a page of conflicting instructions.
Create the definition
Open Agents and choose Create agent. Enter a name and purpose that explain the job without internal jargon.
Choose a model, then write instructions that cover:
- the role the agent should play;
- the inputs it can expect;
- the process or constraints it must follow;
- the required output format;
- when it should ask for clarification or stop.
Make structured output enforceable
Instructions describe what you want; an output schema makes the shape machine-checkable. Use the agent's output contract when another app or workflow depends on exact JSON. Guest Machines accepts a bounded, object-rooted JSON Schema Draft 2020-12 profile and rejects an invalid schema when the agent is saved.
For example:
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"additionalProperties": false,
"properties": {
"summary": { "type": "string", "minLength": 1 },
"risk_level": {
"type": "string",
"enum": ["low", "medium", "high"]
}
},
"required": ["summary", "risk_level"]
}List every mandatory field in required. Set additionalProperties to false
when undeclared fields must fail; JSON Schema allows them by default. A default
value is descriptive only—Guest Machines neither inserts it nor coerces a value
to another JSON type.
The model provider may use structured generation to help produce a matching answer. Guest Machines still parses one exact JSON object and validates it locally against your original schema. A mismatch fails the run. Passing this check proves structure, not factual accuracy or task quality.
Add capabilities deliberately
Assign only the tools and MCP servers needed for the job. Every capability expands what the agent can do and what you need to test and govern.
Knowledge, environment variables, execution limits, network policy, and delegation rules should reflect the same least-privilege approach.
Test the boundary cases
Use a chat to test realistic input, missing information, invalid input, requests
outside the agent's role, and every important output-schema boundary. Test a
missing required field, a wrong JSON type, an unexpected field when
additionalProperties is false, and any formats or limits you rely on. Inspect
the run's completion evidence when the result is surprising.
Make it reusable
Once the agent is reliable, use it as a pipeline step or team member. Keep its contract narrow enough that another person—or another agent—can predict what it will return.