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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the 4-factor model (magnitude, persistence, volatility, trend) and the 0-100 risk score, which tells the agent what kind of signal to expect.

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?

Three dense sentences, front-loaded with the resource and method before the use case. Every sentence carries information, though the method/return details could be trimmed given an output schema exists.

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 an output schema covering the risk score and metrics, annotations covering safety/idempotency, and a single fully documented parameter, the description supplies everything an agent needs to select and call this tool correctly.

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?

Only one parameter and schema description coverage is 100%, so the schema already documents the ticker format with examples. The description adds no syntax, format, or constraint detail beyond implying an NZX company; baseline 3 applies when the schema does the heavy lifting.

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 OCI (Other Comprehensive Income) divergence signal for an NZX company') and immediately explains the underlying analysis (gap between net income and total comprehensive income). This is clearly distinguishable from sibling accounting tools like get_earnings_quality or get_accounting_quality.

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?

Gives a concrete triggering condition: 'Use when investigating whether headline earnings mask hidden losses.' That is a clear context for invocation, but it names no alternative or exclusion (e.g., when to prefer get_earnings_quality or get_earnings instead), so the agent must infer sibling routing.

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