calculate_market_response

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds meaningful behavioral context by specifying that the calculation is based solely on local prices and deliberately does not validate fundamentals, disclosing a limitation 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?

The entire description is one tight sentence with no wasted words. The key capability and resource are front-loaded, and the caveat is a compact second clause that earns its place.

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?

With 4 parameters, zero parameter descriptions, and no usage guidance, the context is incomplete despite the output schema covering return shape. An agent would still lack date format, benchmark semantics, and when to prefer this over sibling research tools.

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 description coverage is 0%, so the description needed to compensate for undocumented parameters, but it does not explain ticker, start_date, end_date, or benchmark semantics or formats. The only related detail is the mention of 'local prices,' which does not map to any parameter.

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 opens with a specific verb ('Calculate') and names concrete outputs ('return, volatility and drawdown') plus their data source ('local prices'). This clearly separates it from qualitative siblings like search_research_reports, verify_thesis, and build_research_object, and the closing caveat adds precision about scope.

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 when the tool is appropriate (compute market metrics from local prices) and offers a negative signal ('prices do not validate fundamentals'), but it never names alternatives or states a concrete when-to-use/when-not-to-use decision rule. This is useful but not explicit guidance.

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