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agentfolio_lookup

Retrieve an AI agent's profile from AgentFolio, including bio, skills, trust score, verifications, and wallet addresses, by agent ID or name.

Instructions

Look up an AI agent's profile on AgentFolio. Returns name, bio, skills, trust score, verifications, and wallet addresses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesAgent ID to look up (e.g. "agent_braingrowth"). Can also be an agent name — it will be normalized.

Implementation Reference

  • The handler function for the 'agentfolio_lookup' tool. It calls the API endpoint /profile/{agent_id} and returns the profile data as a formatted JSON string.
    case "agentfolio_lookup": {
      const profile = await api(`/profile/${args.agent_id}`);
      return JSON.stringify(profile, null, 2);
    }
  • The tool registration definition in the TOOLS array, including name, description, and inputSchema (requires agent_id string).
    const TOOLS = [
      {
        name: "agentfolio_lookup",
        description:
          "Look up an AI agent's profile on AgentFolio. Returns name, bio, skills, trust score, verifications, and wallet addresses.",
        inputSchema: {
          type: "object",
          properties: {
            agent_id: {
              type: "string",
              description:
                'Agent ID to look up (e.g. "agent_braingrowth"). Can also be an agent name — it will be normalized.',
            },
          },
          required: ["agent_id"],
        },
      },
  • src/index.js:437-456 (registration)
    The tool is registered with the MCP server via the ListToolsRequestSchema handler (which returns the TOOLS array) and the CallToolRequestSchema handler (which routes to handleTool).
    // List tools
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: TOOLS,
    }));
    
    // Call tool
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
      try {
        const result = await handleTool(name, args || {});
        return {
          content: [{ type: "text", text: result }],
        };
      } catch (err) {
        return {
          content: [{ type: "text", text: `Error: ${err.message}` }],
          isError: true,
        };
      }
    });
  • The 'api' helper function used by the handler to make HTTP requests to the AgentFolio API (https://agentfolio.bot/api).
    async function api(path, opts = {}) {
      const url = `${API_BASE}${path}`;
      const res = await fetch(url, {
        headers: { "Content-Type": "application/json", ...opts.headers },
        ...opts,
      });
      if (!res.ok) {
        const body = await res.text().catch(() => "");
        throw new Error(`AgentFolio API ${res.status}: ${body}`);
      }
      // Guard against HTML error pages returned with 200
      const ct = res.headers.get("content-type") || "";
      if (!ct.includes("application/json")) {
        const body = await res.text().catch(() => "");
        if (body.includes("<!DOCTYPE") || body.includes("<html")) {
          throw new Error(`AgentFolio API returned HTML instead of JSON for ${path}`);
        }
      }
      return res.json();
    }
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It implies a read-only operation but doesn't explicitly state that, nor does it mention rate limits, auth needs, or side effects. For a simple lookup, this is adequate but not thorough.

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, no filler. The most important information (action and return values) is front-loaded. 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 and lack of output schema, the description adequately lists return fields. However, it could mention caching or staleness of data. Overall, it is complete for a straightforward lookup.

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 coverage is 100% for the single parameter. The description adds value by noting that the agent_id can also be an agent name and will be normalized, which is not in the schema.

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 tool looks up an AI agent's profile and lists the specific fields returned. It distinguishes from siblings like agentfolio_endorsements and agentfolio_list_agents, which have different purposes.

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 versus alternatives like agentfolio_search or agentfolio_list_agents. The description lacks context for tool selection decisions.

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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