fmp_quote

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 'real-time and historical' data but doesn't cover critical aspects like rate limits, authentication needs, data freshness, error handling, or response format. For a financial data tool with zero annotation coverage, this leaves the agent with insufficient operational context.

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 concise and front-loaded in a single sentence, efficiently stating the core functionality. It avoids redundancy and wastes no words, though it could benefit from a second sentence for usage context.

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 of financial data retrieval, lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral traits, usage guidelines, or output expectations, leaving the agent under-informed for effective tool 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?

The input schema has 100% description coverage, so the schema fully documents all parameters. The description adds no parameter-specific information beyond implying historical data availability. This meets the baseline of 3, as the schema does the heavy lifting, but the description doesn't enhance parameter understanding.

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 real-time and historical stock quotes from Financial Modeling Prep. Covers US and global markets.' It specifies the action ('Get'), resource ('stock quotes'), and data source ('Financial Modeling Prep'), with market scope. However, it doesn't explicitly differentiate from sibling tools like 'finnhub_query' or 'alpha_vantage_query' that might offer similar financial data.

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. It mentions coverage of 'US and global markets' but doesn't specify contexts, prerequisites, or exclusions. With sibling tools like 'finnhub_query' and 'alpha_vantage_query' present, the lack of comparative guidance is a significant gap.

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