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hkopenai

Hong Kong Finance Data MCP Server

by hkopenai

get_credit_card_stats

Retrieve Hong Kong credit card lending survey results for a specified period. Use start and end dates to get statistics on credit card lending.

Instructions

Get credit card lending survey results in Hong Kong

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_yearNoEnd Year
end_monthNoEnd Month
start_yearNoStart Year
start_monthNoStart Month

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.7

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. 'Get' implies a read-only retrieval, but the description does not disclose data source, update cadence, authentication needs, rate limits, or any behavior beyond the basic purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler. It immediately communicates the resource and geographic scope without unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists and all four parameters are documented in the schema, reducing the description's burden. However, the description gives no usage context, no survey scope or data provenance, and no behavioral details, making it only minimally complete for a statistics retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the parameter descriptions are tautological ('End Year', 'Start Month', etc.). The main description adds no syntax, default behavior, or date-range semantics beyond what the schema already states, so the baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Get credit card lending survey results in Hong Kong.' It is clear enough to separate from siblings like get_credit_card_hotlines or get_business_stats, though it does not explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no conditions for selecting this tool over sibling statistics tools, and no exclusions. Usage is only implied by the tool name and description.

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