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

Annotations already declare readOnlyHint=true, so the read-only behavior is known. The description adds meaningful context beyond annotations: the exact output fields, the calculation methodology, and the daily update frequency. This enriches the agent's understanding of what the tool returns without contradicting the 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 three sentences: the first packs the core purpose and formula, the second lists use cases, and the third notes update frequency. It is dense but every sentence adds value, and the key information is front-loaded. Slightly long due to the formula detail, but still concise for the complexity.

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 read-only, single-optional-parameter tool with no output schema, the description is remarkably complete. It covers what is returned (score, trend, z_score, composite_latest_value, baseline averages), how it is calculated, when to use it, and update cadence. The optional 'days' parameter is fully handled by the schema. No critical context is missing.

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 only parameter, 'days', is fully described in the input schema (including range, optionality, and Gold tier requirement) with 100% schema description coverage. The tool description does not add any additional parameter nuance; it relies on the schema. Therefore, a baseline score 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 begins with 'Returns a 0-100 US gasoline crack-spread pressure score' and details the exact formula (Gulf Coast gasoline spot x 42 minus WTI spot) and output fields (trend, z_score, composite_latest_value, baseline averages). This clearly defines what the tool does and distinguishes it from sibling tools by naming the specific metric.

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 explicitly states when to call: 'Call when the user asks about refining margins, gasoline-versus-crude spreads, pump-price pass-through, or fuel-cost inflation, or when timing fuel purchases, hedges, or CPI energy calls.' It lacks explicit when-not-to-use or alternative tool references, but the use-case guidance is clear and actionable.

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