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mission69b

t2000

by mission69b
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

t2000_rates

Find optimal interest rates for lending assets across protocols to compare with current positions and preview portfolio optimization.

Instructions

Get best available interest rates per asset across all lending protocols. Use alongside t2000_positions to compare current vs best rates. Use with t2000_rebalance (dryRun: true) to preview optimization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • packages/mcp/src/tools/read.ts:98-110 (handler)
    Implementation of the 't2000_rates' MCP tool, which retrieves best available interest rates via the agent's 'rates()' method.
    server.tool(
  't2000_rates',
  'Get best available interest rates per asset across all lending protocols. Use alongside t2000_positions to compare current vs best rates. Use with t2000_rebalance (dryRun: true) to preview optimization.',
  {},
  async () => {
    try {
      const result = await agent.rates();
      return { content: [{ type: 'text', text: JSON.stringify(result) }] };
    } catch (err) {
      return errorResult(err);
    }
  },
);

Tool Definition Quality

A4.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the tool's function (getting rates) and usage contexts, but lacks details on behavioral traits such as rate limits, authentication needs, error handling, or data freshness. The description doesn't contradict annotations, but it's incomplete 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 concise and well-structured in three sentences: the first states the purpose, and the next two provide usage guidelines. Every sentence adds value without redundancy, making it efficient and front-loaded.

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 complexity (simple rate retrieval with no parameters) and lack of annotations/output schema, the description is mostly complete. It explains what the tool does and how to use it with siblings, but could improve by mentioning output format or data scope limitations. It's adequate but has minor gaps.

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 tool has 0 parameters with 100% schema description coverage. The description doesn't need to explain parameters, and it appropriately doesn't mention any. It adds value by explaining the tool's purpose and usage, which is sufficient given the lack of parameters.

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's purpose with a specific verb ('Get') and resource ('best available interest rates per asset across all lending protocols'). It distinguishes from sibling tools like t2000_all_rates by focusing on 'best available' rates rather than all rates, and from t2000_positions by providing rates for comparison rather than current positions.

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?

The description explicitly provides usage guidance by stating when to use this tool: 'Use alongside t2000_positions to compare current vs best rates' and 'Use with t2000_rebalance (dryRun: true) to preview optimization.' This gives clear alternatives and contexts for application.

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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