get_price_history

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions fetching data but doesn't cover critical aspects like rate limits, authentication needs, data freshness, or error handling. For a data retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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?

The description is appropriately sized and front-loaded, starting with the core purpose followed by parameter details in a structured list. It avoids unnecessary fluff, but the parameter explanations could be slightly more concise (e.g., by integrating defaults more seamlessly). Overall, it's efficient with minimal waste.

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?

Given that there is an output schema (which handles return values), the description doesn't need to explain outputs. However, for a tool with 3 parameters, no annotations, and moderate complexity (financial data retrieval), it lacks details on behavioral traits like data sources or limitations. It's adequate but has clear gaps in completeness.

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?

The description adds meaningful context for all three parameters beyond the input schema, which has 0% description coverage. It explains that 'symbol' is for fetching data (e.g., 'SPY', 'AAPL'), 'days' specifies the past days to fetch (with a default), and 'interval' defines candle intervals (e.g., '1d', '1h'). This compensates well for the schema's lack of descriptions.

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 clearly states the tool's purpose: 'Get historical price data (candles) for a symbol.' It specifies the verb ('Get'), resource ('historical price data'), and scope ('candles'), making it easy to understand what the tool does. However, since there are no sibling tools mentioned, it doesn't need to differentiate from alternatives, so it doesn't reach the highest score of 5.

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 provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It only lists parameters without explaining usage scenarios, such as for financial analysis or backtesting. This lack of guidance makes it less helpful for an AI agent in decision-making.

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