stock_zh_a_tick_tx_js

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds that the return is a pandas DataFrame and identifies the data source, but does not disclose any additional behavioral traits such as rate limits, symbol format requirements, or data coverage. No contradiction with 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 a compact docstring with clear param/return sections. It repeats the title in the return line but is not verbose. The URL example provides some context but could be removed for AI consumption without losing essential information.

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?

With no output schema, the description only specifies the return type as pandas.DataFrame and the general content as historical tick data, but does not describe columns, date range, or any limitations. Given the tool's simplicity and strong annotations, it is adequate but leaves gaps for an agent to know the exact structure of the returned data.

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 description for the 'symbol' parameter (0% coverage). The description explains 'symbol' as '股票代码' (stock code) and provides an example URL with 'sz300494', which gives some context. However, it does not explicitly state the required exchange prefix format (e.g., 'sz' for Shenzhen, 'sh' for Shanghai), leaving potential ambiguity for an agent.

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 returns '历史分笔数据' (historical tick data) from Tencent Finance, and the URL shows a specific example. This distinguishes it from sibling tools like stock_zh_a_hist_tx, which provide K-line data. However, the verb is implicit and '分笔' is not explained for agents unfamiliar with the term.

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 guidance on when to use this tool versus alternatives. It does not mention any conditions, exclusions, or when this might be preferred over other stock historical data tools, which is a significant gap given the large number of sibling tools.

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