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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by listing the returned metrics, which informs the agent about the output shape. It does not contradict annotations, and it adds value beyond them.

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 with no filler. It front-loads the core purpose and metric list, then adds the usage context. Every word earns its place, making it efficient and well-structured.

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 single parameter, read-only nature, and existence of an output schema, the description provides all necessary context: what it does, what it returns, and when to use it. No critical information is missing for an agent to correctly invoke the 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 description coverage is 100%, with the parameter 'ticker' already described as 'NZX ticker symbol'. The description adds nothing further about the parameter's format, constraints, or examples. Since the schema fully covers semantics, a baseline score of 3 is appropriate.

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 states a specific verb ('Get') and resource ('stock performance metrics for an NZX company') and enumerates concrete metrics (returns 1d-5y, alpha vs NZX50, volatility, 52-week range, market cap). This clearly distinguishes it from siblings like get_stock_prices or get_metrics, which cover different 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 an explicit use case: 'Use for performance comparison and pay-for-performance analysis.' It does not explicitly name alternatives or state when not to use it, but the stated use case is clear and sufficient for an agent to decide. A minor gap is the lack of explicit exclusions or alternative tool references.

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