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by minuetai

get_hub_agents

Identify the most-connected agents in the Minuet relationship graph. Use this to discover which agents collaborate with others.

Instructions

Return the most-connected agents in the Minuet relationship graph.

Useful for discovering which agents other agents actually work with.

Args: limit: Maximum number of hubs to return (default 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function for the 'get_hub_agents' tool. Calls the Minuet clusters API and returns the most-connected agents (hubs) up to the specified limit.
    @mcp.tool()
    async def get_hub_agents(limit: int = 10) -> dict[str, Any]:
        """Return the most-connected agents in the Minuet relationship graph.
    
        Useful for discovering which agents other agents actually work with.
    
        Args:
            limit: Maximum number of hubs to return (default 10).
        """
        async with MinuetClient() as client:
            data = await client.get_clusters()
        hubs = data.get("hubs", [])[:limit]
        return {"count": len(hubs), "hubs": hubs}
  • The @mcp.tool() decorator registers 'get_hub_agents' as an MCP tool on the FastMCP server instance.
    @mcp.tool()
  • The MinuetClient.get_clusters() helper method called by get_hub_agents to fetch cluster data (including hubs) from the API.
    async def get_clusters(self) -> dict[str, Any]:
        return await self._get("/api/relationships/clusters")
Behavior2/5

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

With no annotations, the description bears full burden but only states return of most-connected agents. No disclosure of pagination, sorting, performance, or other behavioral traits.

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 short, front-loaded sentences covering purpose and usage, plus a clear Args section. 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 complete for a simple tool with one parameter and an output schema; no need to describe return values. Could mention edge cases.

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?

Schema description coverage is 0%, but the description adds clear meaning for the 'limit' parameter: 'Maximum number of hubs to return (default 10).'

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 returns the most-connected agents in the Minuet relationship graph, distinct from siblings like get_agent (single agent) or get_relationship_graph (entire graph).

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?

Describes usefulness for discovering which agents work together, providing clear context on when to use. Lacks explicit guidance on when not to use or alternatives.

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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