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

No annotations are provided, so the description must carry the full behavioral burden. It does disclose a key behavior: returns ok:false when no published allotment result exists. However, it does not mention any other behavioral aspects such as rate limits, authentication, or side effects. For a read-only getter, this is adequate but not comprehensive.

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 concise sentences with no wasted words. It front-loads the core purpose and data fields, then adds the error condition. Every word earns its place.

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 simple tool with one parameter and no output schema, the description covers the main purpose and a key error condition. However, it lacks usage guidance and parameter semantics, which are important for correct invocation. It is adequate but has clear gaps.

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 0%, so the description must explain the stock_code parameter. It only says 'for a stock', which is implicit and does not clarify the format, required syntax, or how to obtain the code. The description adds minimal value over the bare schema property.

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 it retrieves actual Pool A/B allotment tiers for a stock, listing the specific data fields (applied shares, allotted shares, hit pct, expected lots per tier). The word 'Actual' implicitly contrasts with prediction tools like predict_allotment, but it does not explicitly name a sibling or differentiate from get_allotment_result, which could be similar. This is clear but not fully distinguished.

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 guidance on when to use this tool versus alternatives. It does not state conditions like 'use this when you need actual allotment data' or 'instead of predict_allotment'. The agent must infer usage from the tool name and sibling context, which is insufficient.

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