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

With no annotations, the description carries the full burden. It discloses the data source ('tracked postings'), scope ('Alaska public-sector roles'), and output nature (median and percentile). It could add specifics about behavior when no data is found, but overall it provides useful context beyond a simple label.

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 two concise sentences, front-loaded with the main purpose and followed by a usage tip. Every word 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?

For a simple tool with one optional parameter and no output schema, the description covers the essential aspects: what it returns, data source, geographic scope, and parameter behavior. Minor gaps like error handling or output format exist but are not critical for a simple data lookup.

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?

While the schema describes 'role' with an example, the description adds key behavioral semantics: omitting the parameter lists all roles with data. This goes beyond the schema's simple type/description and clarifies the parameter's optional impact.

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 'median and percentile posted salaries for Alaska public-sector roles' computed from tracked postings. This specific verb+resource+scope distinguishes it from sibling tools like get_state_pay, which likely focuses on other pay data.

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 gives a concrete usage instruction ('Omit role to list all roles with data') but does not mention when to use this tool vs alternatives such as get_state_pay or search_jobs. The context is clear but no exclusions or alternative guidance are provided.

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