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t2000_overview

Get a complete snapshot of your AI banking account including balances, investments, yields, and health metrics in one call for comprehensive financial overviews.

Instructions

Complete account snapshot in ONE call — balance, savings positions, investment portfolio, health factor, yield earnings, fund status, and pending rewards. Use this for morning briefings, general account questions, or any time you need the full picture. Prefer this over calling individual tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The 't2000_overview' tool is implemented as a composite MCP tool that calls multiple agent methods (balance, positions, portfolio, etc.) in parallel to provide a full account snapshot.
    server.tool(
      't2000_overview',
      'Complete account snapshot in ONE call — balance, savings positions, investment portfolio, health factor, yield earnings, fund status, and pending rewards. Use this for morning briefings, general account questions, or any time you need the full picture. Prefer this over calling individual tools.',
      {},
      async () => {
        try {
          const [balance, positions, portfolio, health, earnings, fundStatus, pendingRewards] =
            await Promise.allSettled([
              agent.balance(),
              agent.positions(),
              agent.getPortfolio(),
              agent.healthFactor(),
              agent.earnings(),
              agent.fundStatus(),
              agent.getPendingRewards(),
            ]);
    
          const result = {
            balance: balance.status === 'fulfilled' ? balance.value : null,
            positions: positions.status === 'fulfilled' ? positions.value : null,
            portfolio: portfolio.status === 'fulfilled' ? {
              ...portfolio.value,
              positions: portfolio.value.positions.map(p => ({
                ...p,
                ...(p.currentPrice === 0 && p.totalAmount > 0 ? { note: 'price unavailable' } : {}),
              })),
            } : null,
            health: health.status === 'fulfilled' ? health.value : null,
            earnings: earnings.status === 'fulfilled' ? earnings.value : null,
            fundStatus: fundStatus.status === 'fulfilled' ? fundStatus.value : null,
            pendingRewards: pendingRewards.status === 'fulfilled' ? pendingRewards.value : null,
          };
    
          return { content: [{ type: 'text', text: JSON.stringify(result) }] };
        } catch (err) {
          return errorResult(err);
        }
      },
    );
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates that this is a read-only operation (implied by 'snapshot'), aggregates multiple data points in one call, and suggests it's efficient for comprehensive views. However, it doesn't mention potential limitations like rate limits, authentication needs, or data freshness, leaving some behavioral aspects uncovered.

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 front-loaded with the core purpose in the first sentence, followed by usage guidelines. Every sentence adds value without redundancy, making it efficient and well-structured for quick comprehension.

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 (aggregating multiple data points) and lack of annotations or output schema, the description does a good job explaining what the tool does and when to use it. However, it doesn't detail the return format or potential errors, which could be helpful for an agent to interpret results, leaving minor gaps in completeness.

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, so the baseline is 4. The description doesn't need to explain parameters, and it doesn't add any parameter-specific information, which is appropriate 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: to provide a 'complete account snapshot' with specific components listed (balance, savings positions, investment portfolio, etc.). It uses the verb 'complete' and specifies the resource as the account, distinguishing it from sibling tools that focus on individual components like t2000_balance or t2000_portfolio.

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 states when to use this tool ('for morning briefings, general account questions, or any time you need the full picture') and when not to use it ('Prefer this over calling individual tools'), providing clear alternatives by referencing sibling tools implicitly. This gives strong guidance on tool selection.

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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