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list_open_rfqs

Retrieve open request-for-quotes (RFQs) to view active market demand. Use to decide which RFQs to quote as a market-maker.

Instructions

List currently open (ACTIVE) RFQs awaiting market-maker quotes. Read-only.

USE WHEN: acting as a market-maker agent deciding what to quote on, or showing the user live demand. DO NOT USE WHEN: you want your own trade history (use list_my_trades).

Returns a page of RFQs (id, baseToken, quoteToken, side, amount, isBlind, status, expiresAt). To quote, call respond_rfq with the rfqId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number. Default 1.
pageSizeNoPage size, 1-100. Default 20.

Implementation Reference

  • The handler function that executes the list_open_rfqs tool logic. It calls hl.listRFQs (from the HashLock SDK) with status='ACTIVE', passing optional page and pageSize parameters (defaulting to 1 and 20 respectively), and returns the result wrapped in okContent.
    wrapTool(async ({ page, pageSize }) => okContent(
      await hl.listRFQs({ status: 'ACTIVE', page: page ?? 1, pageSize: pageSize ?? 20 }),
    )),
  • Input schema for list_open_rfqs using Zod. Accepts optional 'page' (1-based, min 1) and 'pageSize' (1-100, default 20).
    {
      page: z.number().int().min(1).optional().describe('1-based page number. Default 1.'),
      pageSize: z.number().int().min(1).max(100).optional().describe('Page size, 1-100. Default 20.'),
  • src/index.ts:279-295 (registration)
    Registration of the 'list_open_rfqs' tool on the MCP server. The server.tool() call registers the tool name, description, Zod input schema, and handler function.
    server.tool(
      'list_open_rfqs',
      [
        'List currently open (ACTIVE) RFQs awaiting market-maker quotes. Read-only.',
        '',
        'USE WHEN: acting as a market-maker agent deciding what to quote on, or showing the user live demand. DO NOT USE WHEN: you want your own trade history (use list_my_trades).',
        '',
        'Returns a page of RFQs (id, baseToken, quoteToken, side, amount, isBlind, status, expiresAt). To quote, call respond_rfq with the rfqId.',
      ].join('\n'),
      {
        page: z.number().int().min(1).optional().describe('1-based page number. Default 1.'),
        pageSize: z.number().int().min(1).max(100).optional().describe('Page size, 1-100. Default 20.'),
      },
      wrapTool(async ({ page, pageSize }) => okContent(
        await hl.listRFQs({ status: 'ACTIVE', page: page ?? 1, pageSize: pageSize ?? 20 }),
      )),
    );
  • The wrapTool helper that wraps the handler to catch errors and return structured error envelopes (machine-readable) instead of throwing.
    export function wrapTool<A extends unknown[]>(
      handler: (...args: A) => Promise<ToolContent>,
    ): (...args: A) => Promise<ToolContent> {
      return async (...args: A) => {
        try {
          return await handler(...args);
        } catch (err) {
          return toErrorEnvelope(err);
        }
      };
    }
Behavior4/5

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

No annotations exist, so description carries full burden. Declares 'Read-only', describes return fields, and mentions pagination. Does not detail rate limits or authentication, but is sufficient for typical use.

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?

Description is only 3 sentences, front-loaded with the core purpose. Every sentence provides value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema, the description names the return fields and links to the next logical action (respond_rfq). Pagination is explained, and the tool's role in the workflow is clear.

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 well-described parameters (page and pageSize). Description does not add additional meaning beyond the schema, so baseline score of 3 is appropriate.

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 'List currently open (ACTIVE) RFQs' with specific verb and resource. Distinguishes from siblings like list_my_trades and respond_rfq by mentioning when each should be used.

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

Usage Guidelines5/5

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

Explicitly provides use cases: 'USE WHEN: acting as a market-maker agent deciding what to quote on... DO NOT USE WHEN: you want your own trade history (use list_my_trades).' Also directs to respond_rfq for quoting.

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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