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minuetai
by minuetai

get_agent

Fetch comprehensive details and Minuet relationship data for a specific agent using its canonical identifier (chainId:agentId).

Instructions

Fetch full details for a specific agent, including its Minuet relationships.

Args: agent_id: Canonical identifier in the form chainId:agentId (e.g. 1:6817 for Ethereum mainnet agent 6817).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The MCP tool handler for 'get_agent'. Decorated with @mcp.tool(), it takes an agent_id string, creates a MinuetClient, and delegates to client.get_agent(agent_id).
    @mcp.tool()
    async def get_agent(agent_id: str) -> dict[str, Any]:
        """Fetch full details for a specific agent, including its Minuet relationships.
    
        Args:
            agent_id: Canonical identifier in the form `chainId:agentId`
                (e.g. `1:6817` for Ethereum mainnet agent 6817).
        """
        async with MinuetClient() as client:
            return await client.get_agent(agent_id)
  • The HTTP client helper that sends a GET request to /api/agent/{agent_id} on the Minuet API. This is called by the server handler.
    async def get_agent(self, agent_id: str) -> dict[str, Any]:
        return await self._get(f"/api/agent/{agent_id}")
  • The FastMCP instance ('mcp') is created on this line. The @mcp.tool() decorator on the get_agent function registers it as an MCP tool.
    mcp = FastMCP("minuet-mcp")
Behavior2/5

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

No annotations provided, and description only states 'Fetch' without disclosing behavioral traits such as authentication needs, error handling, or whether the operation is read-only. The term 'Minuet relationships' is unexplained.

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 sentences, front-loaded with purpose, followed by parameter details. No wasted words.

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?

Adequately covers the tool's function and parameter format. Output schema exists, so return values are documented elsewhere. Could mention that agent_id must exist, but not critical for this simple tool.

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?

Adds significant meaning beyond the schema by specifying the format 'chainId:agentId' with an example. Schema had 0% description coverage, so this is crucial.

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?

Clearly states it fetches full details for a specific agent, including relationships. Distinguishes from sibling tools like 'get_agent_relationships' and 'search_agents'.

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?

No guidance on when to use this tool vs alternatives like 'get_agent_relationships' or 'search_agents'. Does not mention prerequisites or error conditions.

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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