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

No annotations are provided, so the description carries the burden. It discloses the data source URL and the scope of the data (current snapshot), which is useful. However, it doesn't disclose whether the data is cached, how fresh it is, or whether it reflects a live scrape versus a precomputed snapshot.

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 a single compact sentence that front-loads the core value ('iGaming job market right now') and then lists the specific data dimensions. The source URL is useful but slightly tacked on; overall it's efficient and scannable.

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 parameterless tool with no output schema, the description covers the main content dimensions and the source. It doesn't describe the return format, but with no parameters and no output schema, the description is reasonably complete for an agent deciding whether to call it.

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 has zero parameters, so there is no schema to compensate for. The description appropriately explains what the returned market data contains, which is the only meaningful semantic content needed for a parameterless tool.

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 provides iGaming job market statistics: open jobs, new this week, companies hiring, and breakdowns by department, country, working language, and work format. It names a specific resource (the market page) and distinguishes it from sibling tools like get_company or get_job, though it doesn't explicitly name a sibling alternative.

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 implies this is the tool to use for current market-level stats, and the sibling list includes market_history, which suggests a temporal alternative. However, it doesn't explicitly state when to use this tool versus market_history or search_jobs, leaving the agent to infer the distinction.

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