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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly discloses the fallback behavior (ok:false for unknown/no result), the placeholder-tier behavior for pre-listing stocks, and clarifies that summary.reallocation is a raw flag, not a discretionary reallocation indicator. These are valuable behavioral nuances beyond what the schema or annotations convey.

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 front-loaded with the main purpose, followed by structured lists of components. Each sentence adds value, particularly the caveats and the clarification of summary.reallocation. It is slightly verbose but remains focused.

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 tool with one parameter, no output schema, and no annotations, the description gives a reasonable overview of the returned data components and one field-level caveat. However, it does not describe the overall response envelope beyond ok:false, nor does it detail all field semantics, leaving some gaps for an agent trying to parse the result.

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?

The schema has 0% description coverage, so the description must compensate for the stock_code parameter. It mentions 'a stock' and pre-listing stocks, but does not explain the expected format (e.g., numeric string, with/without leading zeros) or provide examples. This minimal elaboration adds little beyond the parameter name itself.

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 clearly states that the tool returns full allotment results page data for a stock and enumerates the components (allotment summary, international placing concentration, cornerstone allocation, Pool A/B tiers). It is specific enough to distinguish from narrower siblings like get_allotment_tiers or predict_allotment, although it does not explicitly name them. The lack of an explicit action verb (e.g., 'retrieves') is a minor gap.

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 provides no explicit guidance on when to use this tool versus alternatives such as get_allotment_tiers or predict_allotment. It includes a caveat that pre-listing stocks return placeholder tiers, which is behavioral rather than a recommendation for selection. Consequently, an agent cannot determine how to choose among related tools without additional inference.

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