get_historical

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

No annotations provided, so description carries full burden. It describes the operation as data retrieval, implying read-only, but does not mention any behavioral aspects like authentication, rate limits, or error handling. This is adequate for a simple fetch operation, but lacks detail for 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.

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

Two sentences, no fluff, front-loaded with the core function and use case. Every sentence adds value.

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?

With output schema present and good schema parameter descriptions, the tool description is complete. It explains what the tool does and when to use it effectively for a data retrieval tool.

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?

All four parameters have descriptions in the input schema (100% coverage). The tool-level description does not add additional meaning beyond the schema, meeting the baseline. The schema descriptions are sufficiently detailed (format, defaults, example).

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?

Description clearly states it gets historical OHLCV price data for a Saudi stock over a date range, and explicitly points to use cases like past prices, trends, or chart data. This distinguishes it from related tools like get_quote or get_financials.

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?

Description explicitly says to use when user asks for past prices or chart data. It doesn't specify when not to use or name alternatives, but the context is clear given sibling tools like get_quote for current prices.

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