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list_services

Discover available service categories in the SOMA marketplace to identify what tasks and assistance you can request from human agents.

Instructions

List what Soma can do. Returns available service categories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The list_services() function that implements the tool logic. It returns a descriptive string explaining what Soma (the agent marketplace) can do, including examples of service requests that can be submitted.
    @mcp.tool()
    def list_services() -> str:
        """List what Soma can do. Returns available service categories."""
        return (
            "Soma — agent marketplace (concierge model)\n\n"
            "Submit any request in natural language. Examples:\n"
            "- 'I need a Python script that monitors gas prices on Arbitrum'\n"
            "- 'Review my smart contract for vulnerabilities'\n"
            "- 'Write a blog post about AI agent reputation systems'\n"
            "- 'Help me set up a Lightning node'\n\n"
            "A human concierge reviews, quotes in sats, and delivers.\n"
            "Payment via Lightning Network."
        )
  • server.py:199-199 (registration)
    The @mcp.tool() decorator that registers list_services as an MCP tool. This is part of the FastMCP framework which auto-registers the function based on the decorator.
    @mcp.tool()
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It compensates partially by specifying the return value ('available service categories'), but fails to state whether the operation is read-only, idempotent, or has side effects.

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

Conciseness5/5

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

Two efficient sentences with no redundancy. The first states the action, the second the return value. Every word earns its place.

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 simplicity (zero parameters) and the presence of an output schema, the description is adequately complete. It appropriately summarizes the return value without duplicating the output schema structure.

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

Parameters4/5

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

Input schema has zero parameters, establishing a baseline of 4. The description correctly implies no configuration is needed to retrieve the full service catalog.

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

Purpose4/5

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

States a clear verb ('List') and resource ('what Soma can do' / 'service categories'). Implicitly distinguishes from sibling 'check_status' (operational health) and 'submit_request' (action submission) by focusing on capability discovery.

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

Usage Guidelines2/5

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

Provides no guidance on when to invoke this tool versus alternatives. Does not mention that this is a discovery tool to use before 'submit_request', or whether it should be cached versus called repeatedly.

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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