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

With no annotations, the description carries the full burden and does reasonably well: it discloses the inputs used (KNN forecast, stamp duty, trading fee, transaction levy, FRC levy), the returned quantities (subscription amount, margin interest, expected allocated lots, total cost, break-even move/price), and the exact fallback semantics when oversub/interest_days are None. It omits permissions/auth or determinism caveats, keeping it short of a 5.

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 tight sentences, front-loaded with purpose, then derivation, then default behavior. No filler, though the tax-schedule enumeration is dense and could be trimmed since those names don't map to parameters.

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 10-parameter computational tool with no output schema and no annotations, the description covers purpose, cost components, returns, and two default behaviors, which is near-adequate. It falls short on the ambiguity between fee and platform_fee and on the margin parameters, where an agent could easily misconfigure the call.

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% across 10 parameters, so the description must compensate, but it only clarifies oversub and interest_days defaults. It leaves fee (which coexists ambiguously with platform_fee), lots, use_margin, margin_rate, margin_ratio, and commission_rate undocumented, so several non-obvious parameters remain guesswork.

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+resource+scope: 'IPO subscription cost and break-even for one stock at a given lot count.' It also explains the two-component derivation (KNN expected-lot forecast + HK sell-side tax schedule), which clearly separates it from siblings like predict_allotment or get_allotment_result.

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?

Usage is implied by the computation described (you run it when you want the all-in cost and break-even for a subscription), but it never states when to prefer it over predict_allotment, get_allotment_tiers, or get_frozen_calendar, nor any prerequisites. The default-explanation sentences describe behavior, not tool selection.

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