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

Annotations already declare readOnly=true, destructive=false, so safety is covered. The description adds real behavioral context beyond annotations: the price vs priceAmount distinction and the instruction to 'Pass priceAmount, never price' guards against a write-time error. It could say more about pagination or auth, but the return-shape disclosure is genuinely useful with no output schema.

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?

Three sentences, front-loaded with what the tool returns, then the precondition, then the critical price/priceAmount caveat. Every sentence earns its place with no filler.

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?

With no output schema, the description fully describes the return shape (choices, prices, defaults, linked categories with rules) and even warns about the price format mismatch when writing back. Nothing needed to call this correctly 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 single param modifierId is documented ('Modifier id from get_modifiers'), so the schema carries the load. The description adds no further meaning for the parameter, making the baseline 3 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?

States a specific verb and resource ('One modifier in full') and enumerates exactly what comes back: choices with prices and defaults, plus every linked category with its own rules. This clearly distinguishes it from the sibling list tool hub_get_modifiers.

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?

Explicitly tells the agent when to use it: 'Read this before editing — update_modifier REPLACES the whole choice list, so you need the current one to send back.' This names the alternative (update_modifier) and the workflow condition that selects this read.

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