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

No annotations are provided, so the description carries the behavioral burden. It adds real value by disclosing the default fallback behavior (alpha=None and oversub=None) and the return shape ('Pool A/B tier expected lots and hit pct'). It does not discuss side effects or auth, but 'Predict...Returns' strongly implies a read-only computational operation.

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 terse sentences: a front-loaded purpose statement, a defaults clause, and a return-value clause. Every sentence earns its place with no filler or redundant restatement of the schema.

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, no annotations, and an empty input schema, the description must do the heavy lifting, and it mostly does: purpose, key overrides, defaults, and output are all covered. Remaining gaps are the meaning of 'agent' parameter values and what 'cibo' refers to, but for a prediction tool the core usage is complete.

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 compensate. It explains alpha and oversub meanings and their None defaults, which is genuinely helpful. However, the 'agent' parameter is never explicitly explained as a model selector, and stock_code is only obvious from its name, not from the description.

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 opens with 'Predict IPO allotment success' – a specific verb and resource – and narrows the scope with 'arbitrary final oversubscription multiple and allocation-method alpha'. It is clear enough to distinguish intent from retrieval siblings like get_oversub or get_allotment_result, though it never names or explicitly contrasts those siblings.

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 phrase 'arbitrary final oversubscription multiple and allocation-method alpha' signals this is for custom/hypothetical scenarios, and the None-default behavior clarifies when the tool falls back to its own or cibo's predictions. It provides clear context but no explicit alternatives or exclusion rules.

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