Full per-stock IPO analysis: subscription rates, allotment tiers, PnL scenarios, CCASS demographics, narrative, plus cross-market context.
Returns ok:false when the stock code is unknown. Note: the analysis
`data.s.reallocation` flag means *discretionary* reallocation (not the
raw clawback flag), and may disagree with get_allotment_result's
summary.reallocation.
| Name | Required | Description | Default |
|---|---|---|---|
| stock_code | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does disclose meaningful behavior: it returns ok:false for unknown stock codes and clarifies that the data.s.reallocation flag means discretionary reallocation, potentially disagreeing with get_allotment_result. It doesn't cover permissions, rate limits, or data freshness, but the error behavior and semantic caveat are substantive.
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 compact and front-loaded with the component list, followed by error behavior and a caveat. Every sentence adds information, though 'plus cross-market context' is slightly vague. Overall it is well-structured with no filler.
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 single-parameter analysis tool with no output schema, the description covers the main output components, the failure mode, and a key semantic warning. It lacks stock_code format details and usage routing, but it is largely sufficient for an agent to invoke the tool correctly.
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 single stock_code parameter has 0% schema coverage, and the description adds no format, example, or accepted-value guidance. The parameter name is self-explanatory, but the description does not compensate for the missing schema documentation.
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 identifies the resource as 'per-stock IPO analysis' and enumerates its components (subscription rates, allotment tiers, PnL scenarios, CCASS demographics, narrative, cross-market context). It lacks an explicit verb and doesn't contrast with sibling tools like get_allotment_result or get_stock_narrative, but the scope is unambiguous.
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?
No guidance is provided on when to use this tool versus alternatives. The only sibling mention is a caveat about data disagreement with get_allotment_result, not a routing rule. The 'Full per-stock IPO analysis' label implies a comprehensive use case, but exclusions and alternative selection criteria are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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