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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description goes further by defining the two returned measures (holdings change in naira/market value, share change in percentage points) and warning that a holdings change mixes new money with price moves rather than being a flow — genuinely useful interpretive context with no output schema available.

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 filler, and the output semantics are front-loaded before the caveat. Every clause carries meaning.

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 no output schema, the description carries the burden of explaining the return shape, and it does so adequately (measures, units, ranking order). It is a read-only, one-parameter tool, so little else is needed; only the tie to sibling tools for cross-queries is absent.

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% for the single optional 'period' parameter, including the default (latest). The description's 'One month' phrasing loosely implies the period argument but adds no format or behavior beyond the schema, 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?

The description names the resource (pension holdings/share by asset class) and the exact scope (one month, versus the month before, ranked largest rise to largest fall), so an agent knows what data comes back. It never states a verb or explicitly distinguishes itself from siblings like get_pension_allocation, leaving that differentiation to inference.

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?

There is no when-to-use or when-not-to-use guidance, and no sibling is named as an alternative. The month-over-month framing hints at a rotation/diff use case, but the agent must infer that on its own.

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