get_ticker

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it returns structured data (including AI-generated analysis and forecasts), throws an error for unrecognized tickers, and notes conditional availability of certain fields (e.g., 'when available'). However, it omits details like rate limits or authentication needs.

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 well-structured and front-loaded with the core purpose, followed by detailed return values and parameter explanation. While comprehensive, some sentences could be more concise (e.g., listing return fields is lengthy but necessary). Overall, it avoids waste and maintains clarity.

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 tool's complexity (returns extensive data) and the presence of an output schema, the description is complete enough. It thoroughly details return values, parameter semantics, and error behavior, compensating for the lack of annotations and low schema coverage, making it self-sufficient for agent use.

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 significant meaning beyond the input schema, which has 0% coverage. It explains the 'ticker' parameter with examples (e.g., 'AAPL', 'BTC'), clarifies it's for stocks, ETFs, or crypto, and notes error behavior for unrecognized symbols, fully compensating for the schema's lack of documentation.

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 with specific verbs ('Get comprehensive data') and resources ('stock, ETF, or crypto ticker'), distinguishing it from siblings like get_option_price or search_news. It precisely identifies what data is retrieved, making the purpose unambiguous.

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 by specifying the tool returns comprehensive ticker data, but it lacks explicit guidance on when to use this tool versus alternatives like get_option_price or search_news. No exclusions or prerequisites are mentioned, leaving usage context inferred rather than clearly defined.

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