Lists valid constants for A-share tool parameters, optionally filtered by kind (frequency, adjust_flag, year_type, index), so you can choose correct values before calling other tools.
List valid constants for tool parameters.
Args:
kind: Optional filter: 'frequency' | 'adjust_flag' | 'year_type' | 'index'. If None, show all.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions listing constants but doesn't disclose behavioral traits like whether it's read-only, the format of returned data, potential rate limits, or authentication needs. This leaves significant gaps for a tool that likely provides reference data.
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 appropriately sized and front-loaded, with a clear purpose statement followed by parameter details in two sentences. There is no wasted text, making it efficient and easy to parse.
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?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate but incomplete. It covers the purpose and parameter semantics well, but lacks behavioral context and usage guidelines, which are important for a reference tool in a financial data context.
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?
With 0% schema description coverage and 1 parameter, the description compensates well by explaining the 'kind' parameter as an optional filter with specific values ('frequency', 'adjust_flag', 'year_type', 'index') and default behavior (show all if None). This adds meaningful semantics beyond the bare schema.
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 the tool's purpose with the verb 'List' and resource 'valid constants for tool parameters', making it specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_index_constituents' or 'list_industries' that might also list data, though their domains differ.
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, such as for parameter validation or data lookup. It mentions an optional filter but doesn't explain scenarios where filtering is beneficial or when to use other tools for similar purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.