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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds the content shape (which pay components appear), which is useful, but says nothing about coverage limits such as whether figures are absent when a company does not disclose, and an output schema already exists so return-value detail is partly redundant.

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 sentences, no waste, resource scope front-loaded and the intended use placed second. Every clause earns its place with no filler.

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 read-only single-company lookup with a fully described 3-parameter schema and an output schema, the description supplies enough to call it correctly: entity scope (NZX), subject (executives) and purpose. Only the sibling-routing detail is missing.

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%, so ticker, role and year are already documented in the schema with format examples ('CEO', '2020-2024'). The description adds no filtering syntax, defaulting, or interaction semantics beyond that, so the baseline 3 applies.

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?

States a specific verb and resource ('Get CEO and executive compensation for an NZX company') and enumerates the fields returned (base salary, STI, LTI, total compensation, shares granted). It is distinguishable from generic peers, but it never names the close siblings get_compensation_benchmark or get_remuneration_benchmarks, so the agent must infer the boundary on its own.

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?

'Use this for pay analysis and pay-for-performance questions' gives a clear positive context for invocation. However, there is no when-not guidance and no routing to the remuneration/compensation benchmark siblings, which is where an agent is most likely to choose the wrong tool.

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