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

With no annotations, the description carries the full burden and does so well: it discloses output field semantics, units (元), sign conventions (main_sell negative), weighted average price fields, historical vs real-time behavior, institutional-only access, and explicit scope exclusions (not order queue, not orderbook).

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 dense but front-loaded with the core purpose and usage trigger. The lengthy enumeration of row fields duplicates the output schema, so a small amount of redundancy keeps it from a 5, but the structure and emphasis markers make it scannable.

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?

Given a complex financial data tool with an output schema and no annotations, the description is complete: it covers purpose, usage, alternatives, parameter behavior, output semantics, access limitations, and scope exclusions. Nothing an agent needs to call it correctly appears to be missing.

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 100%, so both parameters are already documented. The description re-emphasizes the `date` default behavior and code format, but adds little semantic detail beyond what the schema already provides.

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 (拆分/decompose) and resource (L2 主力四分解, minute-level main-buy/main-sell decomposition into active/passive components). It explicitly distinguishes itself from the sibling `ashare_bigorder_flow`, so an agent can tell them apart without opening schemas.

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?

Gives explicit user-question triggers ('主力主动买多少、被动买多少/是扫货还是被砸/买卖均价多少'), names the alternative `ashare_bigorder_flow` and the condition that selects it, explains date-param behavior (historical vs real-time), and warns what the tool is not (order queue / orderbook).

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