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

With annotations already declaring readOnlyHint=true and openWorldHint=false, the description adds valuable context beyond these: data source (NielsenIQ/IRI), update frequency (daily), historical depth (to 1995), and return components (score, trend, confidence, top_drivers). It also clarifies the optional 'days' parameter behavior indirectly through the 'history' mention, and does not contradict the read-only annotation.

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 dense yet efficient, using two sentences plus a closing fragment to convey purpose, methodology, output fields, use cases, data source, update frequency, and historical depth. It is front-loaded with the key purpose and avoids filler or repetition, earning every character.

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?

Given that there is no output schema, the description compensates by listing the output components and providing context on data source, update cadence, and available history. It covers the key operational aspects for a single-purpose metric tool with one optional parameter, making it effectively self-contained for an agent to invoke correctly.

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?

The schema covers all parameters (one optional 'days' parameter with a complete description including Gold tier requirements and fallback behavior), so the schema carries the full weight. The description itself does not elaborate on parameters, but with 100% schema coverage, the baseline of 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 shelf-share velocity score benchmarking distribution efficiency against category leaders' and specifies the output components (score, trend, confidence, top_drivers). It is specific about the resource and what is computed, with enough detail to differentiate it from generic data tools in the adw family.

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?

The description provides explicit when-to-use guidance: 'Call when the user asks about shelf share, distribution velocity, or SKU benchmarking, or when timing planogram resets, trade-promotion spend, or delist decisions.' However, it does not mention when not to use it or point to any alternative tools, so it stops short of a full 5.

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