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PaulieB14

Limitless MCP

get_trader_profile

Retrieve a trader's complete profile from on-chain data, including trade count, volume, fees, PnL, and activity timestamps across both simple and negrisk markets.

Instructions

Get a trader's profile across both simple and negrisk markets. Shows trade count, volume, fees, PnL, and first/last trade timestamps from on-chain data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesTrader wallet address

Implementation Reference

  • The get_trader_profile tool is registered and implemented directly in mcp-server/src/index.ts. It queries both simple and negrisk market subgraphs using a provided user address and combines the results.
    server.registerTool(
      "get_trader_profile",
      {
        description:
          "Get a trader's profile across both simple and negrisk markets. Shows trade count, volume, fees, PnL, and first/last trade timestamps from on-chain data.",
        inputSchema: {
          address: z.string().describe("Trader wallet address"),
        },
      },
      async ({ address }) => {
        try {
          const addr = address.toLowerCase();
          const userQuery = `{
            user(id: "${addr}") {
              id tradesCount totalVolumeUSD totalFeesUSD realizedPnlUSD
              firstTradeAt lastTradeAt
            }
          }`;
    
          const { simple, negrisk } = await queryBoth(userQuery, userQuery);
          const s = simple.user;
          const n = negrisk.user;
    
          if (!s && !n) {
            return textResult({ found: false, message: "No trading activity found for this address" });
          }
    
          const combined = {
            address: addr,
            tradesCount:
              parseInt(s?.tradesCount || "0") + parseInt(n?.tradesCount || "0"),
            totalVolumeUSD:
              parseFloat(s?.totalVolumeUSD || "0") + parseFloat(n?.totalVolumeUSD || "0"),
            totalFeesUSD:
              parseFloat(s?.totalFeesUSD || "0") + parseFloat(n?.totalFeesUSD || "0"),
            realizedPnlUSD:
              parseFloat(s?.realizedPnlUSD || "0") + parseFloat(n?.realizedPnlUSD || "0"),
            firstTradeAt: [s?.firstTradeAt, n?.firstTradeAt]
              .filter(Boolean)
              .sort()[0] || null,
            lastTradeAt: [s?.lastTradeAt, n?.lastTradeAt]
              .filter(Boolean)
              .sort()
              .reverse()[0] || null,
          };
    
          return textResult({
            combined,
            simpleMarkets: s || null,
            negriskMarkets: n || null,
          });
        } catch (e) {
          return errorResult(e);
        }
      }
    );
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses data source ('on-chain data') and market coverage. However, lacks details on error handling (e.g., unknown address), caching behavior, or rate limits that would be expected for a data retrieval tool with no annotation safety hints.

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 well-structured sentences. Front-loaded with the action verb. First sentence establishes scope; second lists specific returned metrics. No redundant words or repetition of structured data elements.

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?

Compensates well for missing output schema by enumerating return fields (trade count, volume, fees, PnL, timestamps). Sufficient for a single-parameter lookup tool. Deducted one point for not describing error cases or empty result behavior.

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

Parameters3/5

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

Schema coverage is 100% with the 'address' parameter already described as 'Trader wallet address'. The description aligns by referencing 'trader' and 'on-chain data' but adds no additional format constraints (e.g., checksum requirements) or usage guidance beyond the schema definition.

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?

States specific action ('Get'), resource ('trader's profile'), and scope ('across both simple and negrisk markets'). Distinguishes from siblings like get_trader_trades and get_trader_positions by specifying aggregated output fields (trade count, volume, fees, PnL) rather than individual records.

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

Usage Guidelines3/5

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

Implicitly guides via listed output fields (use when needing aggregated stats), but lacks explicit when/when-not guidance or named alternatives. Does not clarify when to prefer this over get_top_traders or get_trader_positions despite clear functional overlap.

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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