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

Adds real behavioral context beyond annotations: it will be asked on every engine in the plan from the next run, counts toward the plan's question limit, and duplicate calls return the existing question. Annotations already flag idempotentHint=true and destructiveHint=false, so the description usefully confirms and expands that with the practical consequence.

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 tight sentences, front-loaded with the action and effect. Every sentence earns its place: impact, limit, and idempotency behavior.

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 a 4-parameter write tool with no output schema and full schema coverage, the description covers the key concerns: what happens on call, cost implications, and duplicate handling. Could mention confirm_new_engines gating more explicitly, but the schema already handles that.

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% – all four parameters are documented in the schema, including the buyer-phrasing guidance for text and the confirm_new_engines semantics. The description doesn't add syntax or format details beyond the schema, so 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 (Adds) and resource (a buyer question to a topic), plus downstream behavior. Distinguishes from siblings like add_brand by naming the object and the product surface (Proofsource) clearly.

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?

Explains the effect of adding (asked on every engine from next run) and notes idempotent re-calls. Doesn't name a specific alternative tool to use instead, but the idempotency note and impact statement give strong context for when to use it.

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