stock_hot_rank_detail_realtime_em

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side effects. The description adds return type (pandas.DataFrame) and parameter format (securities code with market prefix), which is useful. However, it does not disclose what the DataFrame contains beyond 'real-time change', nor any data freshness or update behavior, so it adds only modest context beyond annotations.

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, using a four-line docstring format with title, source URL, parameter semantics, and return type. There is minimal fluff, and key information is front-loaded. The return line is terse but acceptable given the simplicity of the tool.

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 single-parameter read-only tool with good annotations, the description covers the essential invocation details. However, the return is described only as '实时变动' (real-time change), which is vague, and there is no explanation of how this differs from closely named siblings like stock_hot_rank_detail_em. An agent might not confidently choose this tool 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 has no parameter description, but the description explains that symbol is a securities code with market representation (e.g., SZ000665) and provides an example URL. This directly compensates for the schema's 0% coverage, though it does not enumerate all possible market prefixes (e.g., SH, BJ), keeping it from a 5.

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 identifies the tool as providing East Money individual stock popularity ranking real-time changes, with a source URL for context. The verb is implicit (get/retrieve), but the resource and real-time nature are clear. It does not explicitly differentiate from sibling tools like stock_hot_rank_detail_em beyond the word 'realtime', so it stops short of a 5.

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 gives no guidance on when to use this tool vs alternatives. There is no mention of sibling tools, exclusions, or context such as 'use for real-time changes; use stock_hot_rank_detail_em for historical'. The only hint is the tool name and the '实时变动' label, which is insufficient.

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