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

With no annotations provided, the description carries the full burden. It discloses the tool is read-only, states the exact output scope (code and name only), and explicitly flags what it does NOT return (market data). It also gives workflow guidance, though it does not mention auth, rate limits, or error behavior.

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 short sentences, front-loaded with the purpose and the critical scoping warning. Every sentence earns its place: what it does, when to use it, what it lacks, and what to do next.

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?

The tool is simple with one parameter, an output schema exists, and the description covers invocation, output scope, read-only safety, and next-step routing. An agent has everything needed to call and sequence this tool correctly.

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 coverage is 100% and the parameter description already includes meaningful examples like '太极实业' or '600667'. The description reinforces that q represents a fuzzy query for disambiguation but does not add substantial new meaning beyond the 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?

Description states a specific verb and scope: search over stocks/funds/sectors for fuzzy term disambiguation. It clearly identifies the core job — confirming the code when the user only gives a name — and differentiates itself from quote/kline tools by saying it returns only code and name.

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?

Explicitly says to use this tool first when the user provides only a name, and explicitly tells the agent to switch to ashare_quote or ashare_kline after obtaining the code. It also excludes the quote use case by warning that this tool does not include market data.

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