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

Annotations already provide safety traits (readOnlyHint, idempotentHint, etc.). Description adds valuable context: source (Eastmoney datacenter) and keyless access, no contradictions. Fulfills behavioral disclosure beyond 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?

Three sentences with front-loaded key information (what it does, metrics, and example query). No redundant or unnecessary text.

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?

Despite no output schema, description lists all returned fields (consensus EPS, P/E, net profit, total revenue). Combined with annotations (readOnlyHint, etc.), it provides a complete picture for a simple data retrieval tool.

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?

Only one parameter 'symbol' with 100% schema coverage. Description reinforces that it's a Chinese A-share code and gives example in query form, but does not add significant new meaning beyond schema description.

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?

Description clearly states it provides analyst consensus estimates for Chinese A-share stocks, listing specific metrics (EPS, P/E, net profit, revenue) per forecast year. It distinguishes from siblings like 'ashares_earnings_forecast' by focusing on consensus estimates from Eastmoney datacenter.

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?

Provides a typical query example ('analyst estimates / 盈利预测 / forecast EPS for a China A-share like 000988'), indicating when to use. Does not explicitly exclude alternatives or mention when not to use, but context is clear enough for an AI agent.

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