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Glama

get_required_reserve_ratio_data

Retrieves required reserve ratio data by date range and year type, helping users analyze monetary policy and liquidity conditions in China's A-share market.

Instructions

Required reserve ratio data.

Input Schema

NameRequiredDescriptionDefault
limitNo
formatNomarkdown
end_dateNo
year_typeNo0
start_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

D1.5/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to do so. It doesn't indicate whether this is a read-only operation, what permissions might be required, if there are rate limits, what the output format or structure looks like, or any side effects. The description is too vague to provide meaningful behavioral context beyond the implied data retrieval.

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

Conciseness3/5

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

The description is extremely concise—a single phrase—but this brevity comes at the cost of under-specification rather than efficient communication. While it's front-loaded with the core topic, it lacks the necessary detail to be helpful. The structure is minimal but fails to convey essential information, making it inefficient in practice.

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

Completeness1/5

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

Given the complexity of a 5-parameter tool with no annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain the tool's purpose in detail, provide usage guidelines, disclose behavior, clarify parameters, or describe output. This leaves the agent with insufficient information to effectively select or invoke the tool.

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

Parameters1/5

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

The description provides no information about parameters, while the input schema has 5 parameters with 0% description coverage (only titles like 'Start Date', 'End Date', etc.). This leaves all parameters undocumented in both schema and description. The description doesn't compensate for this gap by explaining what these parameters mean, their expected formats, or how they affect the data retrieval.

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

Purpose2/5

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

The description 'Required reserve ratio data.' is essentially a tautology that restates the tool name with minimal additional information. It indicates the tool retrieves data related to required reserve ratios but lacks a specific verb (e.g., 'retrieve', 'fetch', 'list') and doesn't clarify what kind of data (e.g., historical values, current rates, time series) or distinguish it from sibling tools like get_deposit_rate_data or get_money_supply_data_year, which might involve related financial metrics.

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

Usage Guidelines1/5

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. It doesn't mention any context, prerequisites, or exclusions, nor does it reference sibling tools for comparison. This leaves the agent with no information to make an informed choice among the many data retrieval tools available on the server.

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