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

With no annotations provided, the description carries the full burden and does so well. It discloses the data source (Yahoo Finance), update frequency (every 2 minutes during market hours), the credit cost (1 credit per call), and the exact return fields (symbol, price, change, changePercent, volume, timestamp).

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

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

Three purposeful sentences front-load the core purpose and usage condition, then cover return fields, data source, refresh cadence, and cost. No filler or redundancy; every sentence earns its place.

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

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

For a simple read-only tool with one optional parameter and no output schema, this description is complete. It tells the agent what data is returned, how to filter, how fresh the data is, and what the call costs, leaving no critical gap for correct invocation.

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

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

Although schema coverage is 100%, the description adds value beyond the schema by providing a concrete example ('AAPL,MSFT,TSLA,GC=F,EURUSD=X') and clarifying that standard Yahoo Finance ticker format should be used. This helps an agent construct valid symbol lists.

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

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

The description opens with a specific verb and resource: 'Fetch real-time price data for 80+ assets across stocks, ETFs, commodities, and forex.' It clearly differentiates from siblings like get_trading_signals and get_commodity_signals by emphasizing raw price data rather than analytical signals or recommendations.

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

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

The description explicitly states when to use it: 'Use this tool when you need current market prices, daily price changes, or percentage moves.' It also explains how to limit results via symbols, but it does not explicitly name alternative tools or provide when-not-to-use guidance.

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