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Get China liquidity

get_china_liquidity
Read-only

Read the latest Mako-curated PBoC balance-sheet publication (CNY trillions + source URL + as_of_month + note). Public read — suitable for surfacing directly when explaining the China leg of global liquidity. The same value is also embedded in get_financial_conditions.pillars.global_liquidity.components.china; this tool exists for direct/auditable access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowNo
statusNo
terms_glossaryNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context beyond that by labeling it a 'Public read' and noting the data is Mako-curated, which tells the agent that no auth is needed and that the source is curated rather than raw. It doesn't discuss rate limits or failure behavior, but those are not critical for a zero-parameter read tool.

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?

Three sentences with no wasted words. The first sentence states the resource and output components, the second gives usage context, and the third names the alternative and the reason for the standalone tool. Everything earns its place.

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?

The complexity is low: no parameters, read-only annotations, and an output schema is present so the return structure is already defined. The description covers the source, the public nature, the intended use case, and the relationship to a sibling tool, which provides a complete picture for an agent deciding whether and how to call it.

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

Parameters4/5

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

The tool has zero parameters, so schema coverage is trivially 100% and there is nothing for the description to document. The description instead usefully enumerates the output fields, which helps an agent understand what the return value contains. The baseline for a no-parameter tool is 4.

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

Purpose5/5

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

The description clearly identifies the exact resource: 'the latest Mako-curated PBoC balance-sheet publication,' and lists its contents (CNY trillions, source URL, as_of_month, note). It also distinguishes itself from the closely related get_financial_conditions tool by explaining the relationship and the specific reason for this standalone tool.

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 explicitly names get_financial_conditions as a place where the same value is embedded and states that this tool exists 'for direct/auditable access.' It also gives a clear suitable scenario ('when explaining the China leg of global liquidity'), though it does not explicitly state when not to use it.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools target clearly distinct resources—regime, liquidity, conditions, prices, ETF profiles, data health—and the three history tools are explicitly separated as price, flow, and judgment. The main ambiguity is get_chapter vs run_chapter, which both return chapter framework content and differ only in usage logging, though the descriptions call this out explicitly.

Naming Consistency4/5

The set follows a consistent snake_case verb_noun pattern: get_ for reads, list_ for enumeration, run_ for framework text, and score_ for position drift. The only wrinkle is run_chapter/get_chapter, where 'run' doesn't mean execution but rather 'return framework text and log usage,' making the verb semantics slightly less predictable.

Tool Count4/5

22 tools is on the heavy side but the set is organized into recognizable clusters: macro regime, liquidity/conditions, histories, portfolio drift, ETF/prices, loops/framework, and data health. Each tool appears to earn its place, so the count is slightly high but not bloated.

Completeness4/5

The surface is comprehensive for a read-and-analyze macro/portfolio server: current reads, historical timeseries, data freshness, event calendar, ETF look-through, drift scoring, and loop navigation are all covered. Minor gaps exist—no direct portfolio/position listing tool and non-US central-bank event dates are intentionally not tracked—but these are acknowledged and workable.

Resources