get_news_dataRetrieve stock-related news for a specific ticker. Provide the symbol and choose how many recent records to receive.
Get stock-related news data.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | Stock symbol/ticker (e.g. '000001') | |
| recent_n | No | Number of most recent records to return |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.2Input schema / additionalPropertiesAdded value: +falsev1.0.0Input schema / properties / recent_n / titleRemoved value: -"Recent N"Input schema / properties / symbol / titleRemoved value: -"Symbol"Output schema / properties / result / titleRemoved value: -"Result"Output schema / titleRemoved value: -"_WrappedResult"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral context. It only says 'get', implying a read-only operation, but provides no details on ordering, date filtering, pagination, or data freshness. It also doesn't warn about any rate limits or access requirements.
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 definition is a single short sentence with no filler, which is efficient for such a simple tool. It is appropriately concise, though the available brevity could have been used to add a bit more 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?
The presence of an output schema and fully documented parameters covers the mechanics of calling the tool. The description is thin on when to use it and what 'news-related' means in practice, but for a simple parameterized GET, it is minimally adequate.
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 fully documents both parameters—'symbol' with an example and 'recent_n' with a default and explanation—so the description adds no additional parameter meaning. Baseline 3 applies because schema coverage is 100%.
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 states a specific verb ('Get') and resource ('stock-related news data'), and this clearly differentiates it from sibling tools like 'get_hist_data' or 'get_realtime_data'. It is not maximally specific about what kind of news data is returned, but it is enough to distinguish the tool's function.
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 about when to prefer this tool over the nine siblings, nor any exclusions or alternative conditions. An agent must infer that it is for news-related queries, but the description never explicitly states this context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.