debt_consolidation

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

With no annotations, the description carries the full burden and does well: it discloses the exact computed outputs (monthly payment, months, total interest, total cost, formula, calculator link) and the non-obvious rule that the origination fee is taken out of the loan so the loan is sized up. 'Education only' scopes the tool as informational, which is an important behavioral caveat for a financial tool.

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?

Four sentences, front-loaded with the core operation then the return values, with the fee rule and the education disclaimer at the end where they belong. No filler, though the return-value enumeration is somewhat list-like.

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?

There is no output schema, so the description must summarize returns, which it does (payment, months, interest, cost, formula, calculator link). Combined with the 100%-documented input schema and the education disclaimer, an agent has enough to invoke and interpret the tool correctly; only the exact return shape (units, field names) is unspecified.

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 100%, so the schema already documents balance, APR, payment, loan_apr, loan_term_months and origination_fee_pct thoroughly. The description adds the 'sized up' interpretation of the origination fee, but that is also present in the schema, so it mostly restates structured data. Baseline 3 is appropriate.

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 names a specific computation (compare current debts against one consolidation loan) and enumerates the inputs and outputs, so the agent knows exactly what the tool produces. It does not explicitly differentiate itself from siblings like credit_card_payoff or loan_cost_by_term, but the scenario is distinctive enough to be distinguishable.

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?

Usage is implied by the scenario ('compare current debts against one consolidation loan') and the 'Education only' disclaimer signals it is a what-if calculator rather than an action tool. However, no alternative tools are named and no explicit when-to-use/when-not-to-use conditions are given.

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