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China Lpr

china_lpr
Read-onlyIdempotent

China's PBOC Loan Prime Rate (贷款市场报价利率, LPR) history — the 1-year and 5-year benchmark lending rates, each with its official reference/announcement date. Published monthly on the 20th (or next business day) by the National Interbank Funding Center under PBOC authorization. The 1-year rate anchors most corporate and consumer loans; the 5-year rate anchors mortgages. Returns up to the last 12 monthly announcements (the publisher exposes only a rolling ~1-year window) plus a latest field for the most recent print. Answers "what is the current PBOC LPR", "China's 1-year and 5-year loan prime rate history", "when did the PBOC last cut the LPR". Keyless, sourced live from the National Interbank Funding Center, under PBOC authorization.

Input Schema

NameRequiredDescriptionDefault
monthsNoHow many of the most recent monthly rows to return, 1-12 (default 12). The upstream only exposes a rolling ~1-year window, so values above 12 are capped at 12.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/openWorld, but the description adds real context beyond them: keyless access, live sourcing from the National Interbank Funding Center, monthly publication on the 20th (or next business day), and — critically — the upstream rolling ~1-year cap on what can be returned.

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?

Front-loaded with the resource and its two rates, then cadence, publisher, and return shape. Dense but nearly every sentence carries information; the parenthetical Chinese name and example questions are justified by disambiguation value.

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

Completeness5/5

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

There is no output schema, and the description compensates by describing the return shape (up to 12 monthly rows plus a `latest` field for the most recent print). With one optional parameter and annotations covering safety, nothing an agent needs to call this correctly is missing.

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% and the single `months` parameter is fully documented in the schema, including the 1-12 cap. The description's mention of the rolling window and 12-row limit echoes rather than extends the schema, so baseline 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?

States a specific resource (PBOC LPR, 1-year and 5-year rates) with scope (history, official dates, monthly cadence) and even example questions it answers. It does not, however, differentiate itself from siblings like china_lpr_latest or china_rates, so an agent must infer which one to pick.

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?

Usage context is clear: current LPR, rate history, and 'when did the PBOC last cut' are all named, which tells the agent when this tool applies. There is no explicit when-not or pointer to the obvious alternative (china_lpr_latest for the current print), leaving that routing to inference.

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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