stock_yjkb_em

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 fully covered. The description adds the return type (pandas.DataFrame) and the upstream data page, but says nothing about latency, pagination, or data freshness beyond what annotations provide.

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 docstring is front-loaded with the source and resource, then the parameter and return type. It is compact with no filler, though the URL line is marginal value and the format is a plain docstring rather than prose tuned for an agent.

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, no-output-schema read tool, the description covers the source, the parameter constraints, and the return type, which is close to sufficient. However, it does not clarify how the returned 业绩快报 differs from related sibling datasets, leaving an agent to infer the distinction.

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 only carries a default value, so the description carries the burden of documenting the lone parameter. It supplies the enum of valid period-end dates and the earliest supported value (20100331), which materially improves correct invocation beyond the bare schema.

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 title/text identifies a specific data source (东方财富, 数据中心) and resource (年报季报-业绩快报), which lets an agent distinguish it from sibling report tools like stock_yjyg_em (预告) or stock_yjbb_em (报表). The verb is implicit ('fetch' the earnings express report) rather than explicit, but the resource is named unambiguously.

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 gives date-format context (quarterly report dates, starting from 20100331), which hints at how to call it, but it never states when to prefer this over sibling tools such as stock_yjyg_em or stock_yjbb_em. Usage is implied by the source/resource naming rather than explicitly guided.

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