nse_quote

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

No annotations are provided, so the description carries the full disclosure burden. It details the return fields (price, change, volume, market cap, P/E ratio, 52-week range, sector) and notes 'and more,' but does not disclose data source delays, rate limits, or potential errors. The examples imply 'live' data, but the description itself is vague about data freshness. This is adequate for a simple quote tool but leaves some unknowns.

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 compact and well-structured: a main sentence, a list of return stats, a parameter explanation, and examples. Every sentence adds value without redundancy. It is appropriately sized for a single-parameter tool and front-loads the main functionality.

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?

For a simple quote tool with one parameter, the description is largely complete. It covers input format and examples, and lists the return fields, which is helpful given no output schema is displayed. It does not cover edge cases like invalid symbols or availability of data, but these are not critical for a basic quote tool. Overall, it provides sufficient context for an agent to select and invoke the 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?

The schema has 0% description coverage (the parameter property 'symbol' has no description). The description compensates fully by explaining the parameter: 'NSE stock symbol (e.g., RELIANCE, TCS, INFY, HDFCBANK, SBIN, ITC)' with multiple examples. This gives an agent clear guidance on what value to supply and the expected format.

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 function: 'Get real-time NSE (National Stock Exchange) quote for an Indian stock.' It uses a specific verb (Get) and resource (NSE quote), and the examples (e.g., 'nse_quote("RELIANCE") → Reliance Industries live price & stats') reinforce the purpose. It distinguishes from siblings like bse_quote by explicitly targeting NSE.

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 establishes clear context: use when you need a real-time NSE quote for a specific Indian stock. It names the input format (NSE symbol) and provides examples. However, it does not explicitly differentiate from other quote tools in the sibling list (e.g., stock_quote, live_quote), so it lacks explicit exclusion or alternative guidance, stopping short of a 5.

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