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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the mutation nature is known. The description adds valuable behavioral context beyond that: the sensitive-tier approval requirement with its 'from-now-on' vs 'just-once' modes, and the timing instruction not to re-ask after the approval card. It also clarifies the domain boundary between offer and feature_index. No contradictions with annotations.

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 definition is front-loaded with the core action and then provides necessary clarifications. Some phrasing is verbose (e.g., 'the operator-authored positioning agents ground all outbound in'), but every sentence serves a purpose: defining the resource, listing parameters, setting boundaries, and explaining approval behavior. It stays within two short paragraphs and remains scannable.

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 destructive mutation with no output schema, the description covers when to call, what to pass, what to avoid, and the approval requirement. It does not describe the tool's return value, but that is often not essential for a state-changing toolcustomarily. The tool is complex (regulated flag, approval tiers, domain boundary) and the description addresses these without relying on external docs.

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 schema already documents all parameters. The description adds real semantics by explaining the purpose of `offer` in context ('what the company sells + the transformation it promises') and `target_summary` ('who it's for'), and crucially instructs what must NOT go into `offer` (features). It does not mention `is_regulated` or `companyId`, but the schema covers them well, so the added value is modest but meaningful.

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 explicitly names the operation ('Author or update the company's grand slam OFFER'), defines the resource (the offer half of the product layer), and states exactly what it sets (`offer`, optional `target_summary`). It also differentiates itself from `create_feature` by declaring that capability truth lives there, not here, making the tool's purpose unmistakable.

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?

It gives explicit situational guidance: 'Call it on the first clear ask; the card is the yes — do not re-ask in chat.' It also tells the agent what NOT to do ('do not list features in the offer') and directly points to the alternative (`create_feature` for capability truth). The approval flow is also explained, leaving no ambiguity about when and how to invoke.

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