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

With no annotations provided, the description must carry the full burden. It discloses the counting-model difference, which is a key behavioral nuance, but does not state whether this is a pure calculation, whether it accesses external pricing data, or what the return format is. It gives some transparency but leaves important operational aspects unspecified.

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 a single sentence that front-loads the core purpose and includes the key differentiator (counting-model difference). It is concise and efficient, though slightly verbose due to the parenthetical clarifications. No wasted words.

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 no output schema and no annotations, the description should explain what the tool returns and any operational constraints. It does not describe the output format or whether it depends on external data, which is a gap for an agent deciding how to use the result. It covers the comparison logic well but leaves the output ambiguous.

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 explains each parameter. The description adds context about workflow volume and the counting-model difference, which helps justify why stepsPerRun and runsPerMonth matter, but it doesn't go beyond the schema in a substantial way. 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 clearly states the tool compares monthly costs on two specific platforms (Zapier and Make) for the same workflow volume, explicitly calling out the counting-model difference. This is a specific verb+resource that distinguishes it from other compare_* siblings like compare_llm_api_costs.

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 (when comparing Zapier vs Make costs at a given volume) but does not explicitly mention alternatives or exclusions. However, the purpose is specific enough that an agent can infer usage without confusion.

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