get_receipt

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds genuine behavioral context beyond that: defaults (empty dates resolve to today, empty vars_list means all products) and the pandas.DataFrame return type. It does not describe scope limits, data source, or latency.

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?

Front-loaded with the subject, then a tight parameter/return block. Given 0% schema coverage, every line adds information an agent needs; nothing is padded.

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 3-param read-only data fetch this is mostly sufficient, and the DataFrame return is named. But with no output schema, the description gives no hint about what the receipt records contain (columns/fields), and it omits any sibling routing, leaving real 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%, so the description carries the full burden and largely delivers: it documents all three parameters, the accepted date formats (YYYY-MM-DD, YYYYMMDD, or datetime.date), the empty-value defaults, and that vars_list holds commodity varieties. Minor mismatch: it types vars_list as str while the schema defines an array.

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?

Title/description state a specific resource: registered commodity warehouse receipt data (注册仓单数据), a clear verb+resource pairing an agent can understand. However, it never distinguishes itself from the exchange-specific siblings such as futures_warehouse_receipt_czce/dce/shfe/gfex, so an agent cannot tell which receipt tool to pick 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?

There is no when-to-use guidance and no reference to any alternative. Given the cluster of warehouse-receipt siblings, the definition provides no routing signal about when this general tool is preferred over them.

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