get_price

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

No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves data (read-only behavior) and mentions two return formats (JSON string or base64-encoded chart), which adds useful context. However, it does not cover potential rate limits, authentication needs, data freshness, or error handling, leaving gaps in behavioral disclosure for a data retrieval tool.

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: the first sentence states the core purpose, followed by a well-structured 'Args' and 'Returns' section with clear bullet points. Every sentence earns its place by providing essential information without redundancy or fluff.

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 the complexity (4 parameters, no annotations, but with output schema indicated by 'Returns'), the description is mostly complete. It explains parameters thoroughly and specifies return formats, but lacks details on output schema structure (e.g., JSON fields) or potential errors. With output schema existence, it need not fully explain return values, but could benefit from more behavioral context.

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 input schema has 0% description coverage, so the description must fully compensate. It provides detailed semantics for all 4 parameters: 'symbol' as ticker symbol with examples, 'interval' and 'period' with valid value lists, and 'visualize' explaining its effect on return type. This adds significant meaning beyond the schema's basic titles and enums.

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 'retrieves historical price data (OHLCV) for a given symbol,' which is a specific verb (retrieves) and resource (historical price data) with the scope (OHLCV format). It distinguishes from siblings like 'get_crypto_price' by specifying historical data rather than current prices, and from 'get_fundamentals' by focusing on price data rather than company metrics.

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 implies usage for historical price data retrieval, but does not explicitly state when to use this tool versus alternatives like 'get_crypto_price' for current prices or 'get_technical_summary' for analyzed data. It provides context (historical data) but lacks explicit guidance on exclusions or comparisons with sibling tools.

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