compute_monetization

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

With no annotations, the description carries the burden; it transparently states the core computation and output shape (score, label, boolean). It doesn't describe scoring rules, label values, edge cases, or whether inputs beyond pricingAnchorsCount are truly optional.

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?

One single sentence, front-loaded with the output and then the inputs; every term earns its place. There is no fluff or repetition of schema details.

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 3-param, no-output-schema compute tool, the description gives the output components and score range plus the input mapping. It is slightly thin on label semantics and formula, but sufficient for an agent to invoke it correctly with the required pricingAnchorsCount.

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 covers dealCycle and modelTags (67%), and the description maps each parameter into the computation: pricing anchors → pricingAnchorsCount, model tags, and deal cycle hint. It adds meaning to pricingAnchorsCount, which the schema does not describe.

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 (Compute), the resource (monetization score), its range (0-21), and the companion outputs label and has_pricing_anchors. The domain clearly separates it from the compute_* siblings, though it does not name an alternative or contrast.

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?

Context is implied: use this when a monetization score is needed from pricing anchors, model tags, and deal cycle. It gives no explicit when-not or alternative routing, and the sibling list contains many compute_* tools, so an agent must infer selection from the name/domain.

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