Get Market History

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

Annotations already declare readOnlyHint=true (safe read operation). The description adds non-contradictory details: 'Analyst tier', data resolutions, and date ranges (early March 2026 onward). This enriches the model's understanding of tool behavior beyond the 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?

Two focused sentences plus example queries. No fluff, front-loaded with key output descriptions. Every sentence adds meaningful guidance.

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 no output schema, the description explains return fields (jobs, remote share, compensation, etc.) and granularity options. It lacks explicit statement that the output is a time-series array, but the text strongly implies it. Adequate for an analyst-tier 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?

Schema coverage is 100%, so baseline is 3. The description adds minor value by specifying actual dates ('back to early March 2026'), complementing the schema's parameter descriptions without duplicating them.

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 explicitly states it provides time-series market-wide hiring stats (jobs, remote share, compensation, etc.), distinguishing it from company-specific tools like get_company_history. It includes concrete use case examples, making the purpose very clear.

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 specific example queries ('how has the market shifted in 2026?'), implying appropriate usage. However, it does not explicitly exclude alternatives or state when not to use this tool vs. siblings like get_market_pulse.

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