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

Annotations provide readOnlyHint and openWorldHint, which the description aligns with. The description adds geographical scope ('across Australian regions') but lacks details on data freshness, pagination, or any side effects, which would improve transparency 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 two sentences, front-loading the core function and then providing usage context. No extraneous words, making it highly efficient.

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?

Given the existence of an output schema, the description appropriately lists return fields without unnecessary detail. It adequately covers purpose, usage, and key aspects for a simple data retrieval tool.

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?

With 100% schema coverage, the schema already documents both parameters. The description does not add new meaning or constraints beyond what is in the schema, so it meets the baseline but does not exceed it.

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 retrieves trade demand hotspots across Australian regions, listing specific data points (demand scores, shortage severity, etc.). It distinguishes itself from sibling formation tools like formation.recommend_trade by focusing on location-based demand 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 explicitly advises using it for advising where to start a trade business, providing clear contextual guidance. However, it does not explicitly mention when to avoid using it or suggest alternative tools, leaving some ambiguity among siblings like formation.location_score.

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