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Glama

get_key_metrics

Read-onlyIdempotent

Retrieve key financial metrics such as P/E, PEG, P/B, EV/EBITDA, margins, ROE, ROA, and growth rates for US, Korean, and Japanese stocks via yfinance.

Instructions

Get key financial metrics summary from yfinance (US, Korea, Japan).

Returns P/E, PEG, P/B, EV/EBITDA, margins, ROE, ROA, growth rates, etc.

Args: symbol: Stock ticker. US: "AAPL", Korean: "005930.KS", Japanese: "7203.T"

Returns: Structured JSON envelope with key financial metrics.

Input Schema

NameRequiredDescriptionDefault
symbolYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare that this is a read-only, idempotent, non-destructive, open-world operation. The description adds useful behavioral context by naming yfinance as the source and identifying the metric categories returned. It does not discuss rate limits, data freshness, or source limitations, so it stops short of full transparency.

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 short and front-loaded, with a clear purpose sentence followed by metrics, args, and returns. The Returns sentence is somewhat redundant because an output schema exists, but overall there is little waste.

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?

For a one-parameter read-only financial data tool with annotations and an output schema, the description covers source, metric scope, supported markets, and symbol format. It is sufficient to invoke the tool correctly, though it omits sibling routing and data freshness caveats.

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 description coverage is 0%, so the description must carry parameter semantics, and it does. It explains that symbol is a stock ticker and gives concrete formats for US, Korean, and Japanese tickers.

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 a clear verb and resource: getting a key financial metrics summary. It also lists representative metrics and supported markets, making the tool understandable. However, it does not explicitly differentiate itself from close siblings such as get_financials, get_ttm_financials, or get_stock_snapshot.

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

Usage Guidelines3/5

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

The listed metrics imply valuation and profitability use cases, and the market examples imply coverage scope. But there is no explicit guidance on when to choose this tool over alternatives like get_financials or get_stock_snapshot. Usage is inferable rather than stated.

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