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Glama

get_money_supply_data_year

Fetch yearly money supply data with date range and limit filters for A-share market analysis. Outputs markdown for easy reporting.

Instructions

Yearly money supply data.

Input Schema

NameRequiredDescriptionDefault
limitNo
formatNomarkdown
end_dateNo
start_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior1/5

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

No annotations are provided, so the description carries full burden. It reveals nothing about behavior: no indication of read/write nature, authentication needs, rate limits, error conditions, or what the output looks like. 'Yearly money supply data' suggests a read operation but lacks confirmation or details.

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?

Extremely concise with a single phrase 'Yearly money supply data.' It's front-loaded and wastes no words, though this brevity contributes to underspecification in other dimensions.

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

Completeness2/5

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

For a 4-parameter tool with no annotations and no output schema, the description is incomplete. It doesn't cover parameter meanings, behavioral traits, or output format, leaving significant gaps for an AI agent to understand and invoke the tool correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It mentions 'yearly' which hints at date parameters but doesn't explain the four parameters (start_date, end_date, limit, format) or their relationships. The description adds minimal value beyond the schema titles.

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

Purpose3/5

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

The description 'Yearly money supply data' states the resource (money supply data) and temporal granularity (yearly), but lacks a specific verb and doesn't distinguish from sibling 'get_money_supply_data_month'. It's vague about what action is performed (retrieve? list? fetch?).

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?

No guidance on when to use this tool versus alternatives like 'get_money_supply_data_month' or other financial data tools. The description implies yearly data but doesn't specify use cases, prerequisites, or exclusions.

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