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

Annotations already mark readOnlyHint=true, and the description adds meaningful behavioral context: the composite formula weights, neutral 50, higher=tighter interpretation, weekly updates, and returned fields. It does not contradict the annotations and provides value beyond them.

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 only two sentences, front-loaded with the definition and immediately followed by actionable call scenarios. Every element, including the formula parenthetical, adds value and there is no filler.

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 data tool with one optional parameter, the description covers index meaning, composition, direction, history, update frequency, output fields, and use cases. The schema fully documents the only parameter, so the description is complete for effective invocation.

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 description covers 100% of the single optional `days` parameter, including the 5-year limit and Gold-tier requirement. The tool description itself does not mention `days`, but with full 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 states a specific verb 'Returns a 0-100 global liquidity stress index' and provides composition, scale semantics, and output fields. It clearly identifies the resource and distinguishes this tool as a liquidity/financial-conditions data query among many numeric siblings.

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 call triggers: 'Call when the user asks about liquidity stress, financial conditions, money-market or funding strain...' and adds practical timing use cases. It does not mention when not to use or alternative tools, but the context is clear enough for selection.

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