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get_unique_traders_by_collection

Retrieve unique buyer and seller counts for NFT collections to analyze trading activity and market participation.

Instructions

Retrieve count of unique buyers and sellers for NFT collections.

Args:
    limit (int, optional): Maximum number of rows to fetch from the query. Defaults to 1000.

Returns:
    str: Markdown table of unique traders by collection, or error message if the query fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Implementation Reference

  • main.py:105-121 (handler)
    The handler function decorated with @mcp.tool() that implements the logic for get_unique_traders_by_collection. It fetches the latest results from Dune query ID 5140464, processes the data into a pandas DataFrame, and returns it as a Markdown table.
    @mcp.tool()
    def get_unique_traders_by_collection(limit: int = 1000) -> str:
        """
        Retrieve count of unique buyers and sellers for NFT collections.
    
        Args:
            limit (int, optional): Maximum number of rows to fetch from the query. Defaults to 1000.
    
        Returns:
            str: Markdown table of unique traders by collection, or error message if the query fails.
        """
        try:
            data = get_latest_result(5140464, limit=limit)
            df = pd.DataFrame(data)
            return df.to_markdown()
        except Exception as e:
            return str(e)  
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context by specifying the return format (Markdown table) and error handling, but lacks details on permissions, rate limits, or side effects. This is adequate but has clear gaps for a tool with no annotation coverage.

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?

The description is front-loaded with the core purpose, followed by structured sections for Args and Returns. Every sentence earns its place, with no wasted words, making it efficient and easy to parse for an AI agent.

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 low complexity (one optional parameter) and no output schema, the description is reasonably complete. It covers purpose, parameter semantics, and return format, though it could benefit from more behavioral context like error conditions or performance notes to be fully comprehensive.

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?

The description adds meaningful semantics beyond the input schema, which has 0% coverage. It explains that 'limit' controls the maximum rows fetched and defaults to 1000, compensating for the schema's lack of descriptions. With only one parameter, this provides sufficient context for agent understanding.

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 the specific verb ('retrieve count') and resource ('unique buyers and sellers for NFT collections'), distinguishing it from siblings like get_average_price_by_collection or get_daily_sales_by_collection. It precisely defines what the tool does without being vague or tautological.

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?

The description provides no guidance on when to use this tool versus alternatives like get_new_owners or other sibling tools. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the purpose alone.

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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