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configure_service

Add a new email service configuration at runtime for immediate email sending and inbox monitoring via SMTP, API, local, or webhook.

Instructions

Configure a new email service dynamically.

Adds a new email service configuration at runtime. The service will be available for sending emails and inbox checking immediately.

Args: name: Unique name for the service (e.g., "my-sendgrid", "dev-mailhog") type: Service type - "smtp", "api", "local", or "webhook" config: Service-specific configuration dictionary enabled: Whether the service should be enabled (default: True)

Returns: Dictionary with configuration result: { "success": bool, "service": str, # Service name "type": str, # Service type "message": str # Success/error message }

Examples: # Configure SendGrid API service configure_service( name="my-sendgrid", type="api", config={ "api_key": "your-sendgrid-key", "api_url": "https://api.sendgrid.com/v3/mail/send", "from_email": "noreply@yourdomain.com", "service_type": "sendgrid" } )

# Configure local MailHog for testing
configure_service(
    name="local-testing",
    type="local",
    config={
        "smtp_server": "localhost",
        "smtp_port": 1025,
        "http_url": "http://localhost:8025",
        "service_type": "mailhog"
    }
)

Notes: - Service names must be unique - Configuration is stored in memory (not persisted) - Use list_services() to see available services

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
typeYes
configYes
enabledNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that configuration is stored in memory (not persisted) and becomes available immediately. It also notes service name uniqueness. Missing details on error handling if name duplicates or if type is invalid, but overall good transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Args, Returns, Examples, Notes). It is front-loaded with the purpose. While slightly lengthy due to examples, the structure and clarity justify the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 params, nested objects, output schema), the description covers parameters, return format, examples, and important notes. It mentions the output schema structure. Missing validation details for 'type' values (e.g., accepted strings) but examples cover common ones.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage. The description provides detailed parameter explanations in Args (name, type, config, enabled) and includes comprehensive examples. This adds substantial meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Configure a new email service dynamically.' with a specific verb and resource. It distinguishes from sibling tools like list_services, send_email, etc., by focusing on service configuration rather than usage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (to add a new email service) and provides notes on uniqueness and persistence. It references list_services() to see available services, implicitly suggesting when not to add a duplicate. However, it lacks explicit alternatives for modifying existing services.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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