plaid-mcp

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it merges data from Plaid and user inputs, ranks debts by strategy, and returns projections and warnings. However, it lacks details on permissions, rate limits, or error handling, which are important for a tool processing financial data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core purpose. Every sentence adds value, such as explaining data sources, strategies, and outputs. It could be slightly more structured with bullet points for clarity, but it avoids redundancy and waste.

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

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

Given the complexity (financial projections with multiple inputs) and no annotations or output schema, the description is fairly complete. It covers purpose, parameters, and return values (balance, interest, projections, warnings). However, it lacks details on output format or error cases, which would enhance completeness for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It effectively explains all three parameters: 'strategy' (avalanche vs. snowball with definitions), 'extra_monthly_payment' (dollars above minimum), and implicitly 'today' (used for projections, though not explicitly named). This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Rank every debt and project payoff timelines.' It specifies the verb ('rank'), resource ('debt'), and scope ('project payoff timelines'), and distinguishes itself from sibling tools like 'get_liabilities_tool' or 'list_external_debts_tool' by focusing on ranking and projections rather than just listing or retrieving data.

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

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

The description provides clear context for when to use this tool: to analyze debt payoff strategies (avalanche vs. snowball) with extra payments. It implies usage for financial planning scenarios. However, it does not explicitly state when not to use it or name alternatives among siblings, such as 'get_liabilities_tool' for raw debt data without projections.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.