get_stock_changes

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

The readOnlyHint annotation already establishes safety, and the description adds the real-time nature of the data ('实时市场信号'), which is useful behavioral context. It does not disclose response format or pagination, but for a read-only tool with this annotation coverage, this is acceptable. No contradiction.

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, front-loaded sentence that states the verb and resource, then provides concrete examples of anomaly types. No wasted words.

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?

The tool is simple with one optional parameter, good annotations, and no output schema. The description covers the purpose and types, but the return format is left unexplained. Given the low complexity, the description is mostly complete, though a note on the response structure would improve it.

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 describes the single 'type' parameter with an enum and default value, covering 100% of parameters. The description provides Chinese translations for a few enum values (e.g., 火箭发射, 大笔买入), adding some semantic meaning beyond the bare English enum, but does not fully document all 22 types. This is a modest enhancement over the schema, earning a baseline 3.

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 retrieves market order flow anomaly data ('获取盘口异动数据') and enumerates 22 anomaly types, differentiating it from sibling tools like get_board_changes (sector-level changes) by focusing on 盘口 (order flow) anomalies.

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 explicit guidance on when to use this tool over alternatives, such as get_zt_pool or get_board_changes, nor does it mention exclusions. The only hint is '捕捉实时市场信号' (capturing real-time market signals), which is too vague to qualify as clear usage guidance.

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