stock_lhb_detail_daily_sina

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 clear. The description adds useful context by specifying the return type as pandas.DataFrame and the parameter as a trading day, but it does not disclose column details, pagination, or data source quirks. 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 brief and front-loaded with the title. It includes a source URL and structured docstring lines for param/return. There is minor redundancy (the title repeats in the 'return' line), but overall it is concise and well-organized for the limited content it provides.

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 no output schema, the description is mostly adequate but thin. It explains the parameter and return type, yet it fails to clarify the DataFrame columns, how this tool differs from the many similar LHB siblings, or any date formatting/rules. The strong annotations partially compensate, but the lack of differentiation in a crowded sibling set leaves gaps.

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 zero description coverage, so the description must compensate. It defines 'date' as '交易日' (trading day) and gives its type as str, which adds semantic meaning beyond the bare schema. The default value '20240222' implies a YYYYMMDD format, but this is not explicitly stated, and no further details about required vs optional behavior are provided.

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 identifies the tool as '龙虎榜-每日详情' (Dragon-Tiger List daily details) and provides a source URL. This conveys that the tool fetches daily LHB details, and the name includes 'sina' to distinguish from similar EM-based tools. However, it lacks a verbose action verb and does not explicitly differentiate among the many sibling LHB tools.

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 exclusions, prerequisites, or comparisons to sibling tools like stock_lhb_detail_em or stock_lhb_ggtj_sina. The only context is the source URL, which does not help an agent choose between similar LHB tools.

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