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

Annotations already establish this as a safe, idempotent, closed-world read. The description adds what annotations cannot: the inverted semantics ('LOWER IS HEALTHIER', 'a rising score means conditions are deteriorating'), which directly prevents an agent from misreading the output. It also supplies the band thresholds needed to interpret the number.

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?

Front-loads the return payload, then the directionality warning, then the escalation path to the indicators tool. Each sentence carries distinct and non-redundant information; nothing repeats the title or annotations.

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?

With no output schema, the description takes on return-value disclosure and does it fully – score, regime label, and layer breakdown are all named. Combined with the risk-direction explanation, an agent has everything needed to call and interpret it 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 tool takes zero parameters, so the baseline of 4 applies and there is nothing for the description to compensate for. Schema coverage is 100% regardless.

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 resource and scope ('Today's Zensei Index for U.S. equities') and enumerates exactly what comes back: final score, regime label, and three named layer scores. Against siblings like zensei_index_history and zensei_index_indicators, the 'today' scoping makes the boundary obvious.

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?

Explicitly routes the agent to zensei_index_indicators to understand drivers, which is a genuine alternative-selection cue. It stops short of naming when to prefer zensei_index_history or zensei_index_summary, so the sibling routing is only partly covered.

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