quote_detail

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 mentions 'detailed' market data but doesn't disclose behavioral traits such as data freshness (real-time vs. delayed), rate limits, authentication needs, error handling, or what 'detailed' includes (e.g., price, volume, bid-ask spreads). This is a significant gap for a data-fetching tool with zero annotation coverage.

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 a single, efficient sentence in Chinese ('获取某支股票的行情数据-详细'), which is appropriately concise and front-loaded with the core purpose. However, it could be slightly improved by specifying what 'detailed' means, but it avoids unnecessary verbosity.

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 tools, no annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't explain the return values (e.g., data structure, fields), error cases, or how it fits among the many sibling tools, making it inadequate for reliable agent use without additional 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 schema description coverage is 0%, so the description must compensate. It implies a stock parameter but doesn't explain the 'stock_code' input beyond what's in the schema (which only has a title and default). No details on format (e.g., exchange prefixes like 'SZ'), valid codes, or handling of invalid inputs are provided, leaving the parameter poorly documented.

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 '获取某支股票的行情数据-详细' (Get detailed market data for a stock) states a clear verb ('获取' - get) and resource ('行情数据' - market data), but it's vague about what 'detailed' entails compared to other tools. It doesn't distinguish from siblings like 'quotec' (which might be a simpler quote tool) or 'kline' (which could provide chart data), leaving the scope ambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'quotec', 'kline', 'pankou'), the description lacks context on whether this is for real-time data, historical data, or specific metrics, and doesn't mention prerequisites or exclusions, leaving the agent to guess based on tool names alone.

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