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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds valuable behavioral context: data lineage (NielsenIQ/IRI, history to 1962), daily updates, and the composition of the score. No contradiction 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 description is extremely concise—two sentences that front-load the core function and output, then immediately give use cases and update frequency. Every word earns its place with no redundancy.

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 tool with no output schema, the description names all key output fields (score, trend, confidence, top_drivers) and clarifies the composite inputs. It also covers use cases and update cadence. The only missing piece is a detailed return structure, but this is not critical given the description's clarity.

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%, and the schema already documents the 'days' parameter thoroughly (optional, history series, Gold tier requirement). The tool description adds no additional parameter semantics beyond mentioning 'daily' and 'history', so 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 returns a '0-100 marketing-mix optimization score by consumer segment' with specific components (score, trend, confidence, top_drivers) and data source. The verb 'Returns' and the explicit '3-Ps Mix Index' scope distinguish it from sibling tools, even without naming them.

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?

Provides explicit when-to-use guidance: 'Call when the user asks about product-price-promotion mix, segment targeting, promo effectiveness, or sales lift, or when timing trade-promotion budgets or price changes.' However, it does not mention when not to use or alternative tools, so it falls short of a 5.

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