calculate_repair_or_replace

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds transparency by fully disclosing the decision logic (the 50% rule) and the factors considered (cumulative repair cost, replacement cost, age, expected lifespan), leaving no hidden behavior.

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 sentences, with the purpose front-loaded and the decision rule compressed efficiently. Every phrase earns its place; no filler or repetition.

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?

Despite no output schema, the description states it 'returns a recommendation' and explains the criteria. Combined with the detailed parameter descriptions and annotations, the tool is fully specified for its calculation purpose.

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%, so the baseline is 3. The description adds semantic value by explaining how the parameters interact (e.g., cumulative repair cost vs. replacement cost, age vs. expected lifespan) and the 50% rule, which is not explicit in the 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 'Run the standard repair-or-replace decision math for a home appliance' and details the basis of the recommendation. It distinguishes the tool from siblings like check_appliance_recall and get_appliance_lifespan, which address different questions.

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 includes 'Use this when a user is weighing whether to fix or replace an appliance,' providing explicit context. It doesn't mention alternatives or exclusions, but the purpose is clear enough to guide correct selection.

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