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

Annotations already declare readOnlyHint=true, and the description adds useful context about the methodology (z-scored vs 36-month window), the meaning of 50, and the update frequency. It does not explicitly mention the Gold tier requirement for history, which is in the schema, but overall it provides meaningful behavioral detail beyond 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 long, front-loaded with the core purpose and output details, followed by use cases and update frequency. Every sentence adds value 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?

The description lists all output fields and explains the score interpretation. While it does not describe the Gold tier requirement for history (the schema does), it is otherwise complete for a read-only tool with a single optional parameter and clear update cadence.

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 coverage is 100%, so the 'days' parameter is fully described in the schema. The main description does not add any additional semantic meaning for the parameter beyond what's in the schema, so the 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 clearly states the tool returns a 0-100 US labor-market tightness score with a specific formula and lists the exact output fields. It also names concrete use cases, effectively distinguishing it from sibling tools even without explicit alternatives.

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 an explicit list of when to call the tool (e.g., labor market tightness, worker shortages, wage pressure, salary-band reviews). However, it does not state when not to use it or mention any alternatives, so it falls 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.