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AgentLadle MCP AKShare

get_interest_rate

Read-onlyIdempotent

Retrieve interest rate data including LPR, SHIBOR, and LIBOR. Specify rate type and optional date range to get historical values.

Instructions

Get interest rate data (LPR, SHIBOR, LIBOR).

Directly invoke with rate_type. get_interest_rate(rate_type="lpr", start="2023-01-01")

Args: rate_type: lpr/shibor/libor start: Start date YYYY-MM-DD (optional) end: End date YYYY-MM-DD (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startNo
rate_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
hintNo
errorNo
cachedNo
sourceNo
statusYes
updated_atNo
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds context by listing the specific rate types (LPR, SHIBOR, LIBOR) and parameter behavior, consistent with annotations. No contradiction.

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

Conciseness4/5

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

The description is concise (one-line purpose, strategy, example, arg list) and well-structured. It could be slightly more streamlined, but every sentence adds value.

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

Completeness4/5

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

Given three parameters (one required), no enums in schema, but description clarifies allowed values and date format. Output schema exists, so return values need not be explained. The description is sufficient for a simple data retrieval tool.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully compensates by explaining rate_type values ('lpr/shibor/libor'), start/end date format ('YYYY-MM-DD'), and optionality. This adds significant meaning beyond the schema's property names and types.

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 'Get interest rate data (LPR, SHIBOR, LIBOR),' specifying the exact resource and scope. It is clear but does not explicitly differentiate from sibling tools like get_macro_data or get_exchange_rate, which could also contain interest-related data.

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

Usage Guidelines4/5

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

The description includes a strategy ('Directly invoke with rate_type') and a concrete example, guiding when to use. However, it does not mention when not to use or provide alternatives, though no sibling tool covers the same domain.

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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