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t2000_contacts

Manage contact name-to-address mappings for AI banking transactions. Use saved contacts instead of raw addresses when sending funds.

Instructions

List saved contacts (name → address mappings). Use contact names with t2000_send instead of raw addresses. Use t2000_contact_add to save new contacts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Implementation of the 't2000_contacts' tool, which lists saved contacts by calling agent.contacts.list().
    server.tool(
      't2000_contacts',
      'List saved contacts (name → address mappings). Use contact names with t2000_send instead of raw addresses. Use t2000_contact_add to save new contacts.',
      {},
      async () => {
        try {
          const contacts = agent.contacts.list();
          return { content: [{ type: 'text', text: JSON.stringify({ contacts }) }] };
        } catch (err) {
          return errorResult(err);
        }
      },
    );
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 states this is a listing operation, which implies it's read-only and non-destructive, but doesn't explicitly confirm safety, permissions, or behavioral details like pagination or error conditions. The description adds some context about how the output is used with t2000_send, but lacks comprehensive behavioral disclosure.

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 extremely concise with two sentences that each serve a distinct purpose: stating what the tool does and providing usage guidance. There's zero wasted text, and the information is front-loaded with the core purpose.

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?

For a simple listing tool with no parameters and no output schema, the description is reasonably complete. It explains the purpose, how to use the output, and when to use alternatives. However, without annotations or output schema, it could benefit from more detail about return format or behavioral constraints, keeping it from a perfect score.

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. Since there are no parameters, the baseline is 4, and the description doesn't detract from this.

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 ('List') and resource ('saved contacts') with additional detail about what's listed ('name → address mappings'). It distinguishes this tool from siblings by mentioning t2000_send and t2000_contact_add, making the purpose highly specific and differentiated.

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 provides explicit guidance on when to use this tool ('Use contact names with t2000_send instead of raw addresses') and when to use alternatives ('Use t2000_contact_add to save new contacts'). This gives clear context for usage versus other tools in the ecosystem.

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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