stock_lhb_yytj_sina

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, covering the safety profile. The description adds the upstream source URL and a pandas DataFrame return type, which is modest context, but says nothing about pagination, row limits, or refresh cadence.

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?

Compact overall, but the ':return:' line merely restates the opening title, and embedding a long source URL consumes space without helping tool selection. The genuinely useful param choices are present, so structure is adequate rather than tight.

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-optional-parameter read tool with no output schema and annotations covering safety, the description supplies param semantics and the return type. It is nearly complete; the missing default value and any row-limit behavior are minor 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?

Schema description coverage is 0% and the schema exposes only a bare string 'symbol', so the description carries the burden. It documents all four allowed values (5/10/30/60 days) with their meanings, which is the key information an agent needs; it omits only the default of '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 names a specific dataset ('龙虎榜-营业部上榜统计') and gives the exact source URL, so an agent knows it retrieves Sina's Dragon-Tiger List brokerage-branch statistics. However, it does not distinguish this from the many close siblings such as stock_lhb_ggtj_sina, stock_lhb_jgzz_sina, or stock_lh_yyb_* variants that all deal with LHB/branch data.

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 when-to-use or when-not-to-use guidance is given, and no alternative tool is named despite a large family of competing LHB tools. The agent must infer the use case purely from the title.

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