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

With no annotations, the description carries the full behavioral burden. It discloses that results are conditional ('when one exists'), includes annual savings and reasoning, and states the legacy→modern bias. It doesn't detail response format or multiple-result handling, but those are minor for this simple 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?

Two dense sentences with no filler. The main action and returned fields are front-loaded, and the parenthetical examples demonstrate the swap bias efficiently.

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?

For one required parameter and no output schema, the description covers the parameter, the conditional result, the cost/savings data, and the reasoning output. It doesn't specify exact response shape or behavior for unknown inputs, but nothing essential is missing.

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 coverage is 100% and the schema already describes 'tools' as names to evaluate. The description reinforces the per-tool iteration but doesn't add format or domain-constraint details beyond the schema. Baseline 3 applies.

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?

States a specific verb (return), resource (StackSwap's AI-native replacement recommendation), and required output (annual savings, reasoning). Examples and 'skews toward legacy → modern swaps' sharpen intent and distinguish it from comparison/audit siblings.

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?

Clear context: take supplied tools and return AI-native replacement recommendations, which tells an agent when to choose this over general compare/audit tools. It does not explicitly name alternatives or conditions to avoid, so it stops short of a 5.

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