Research Grounding

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

With no annotations, the description carries the full burden and does meaningful work: it honestly declares that report bodies have no stable programmatic interface, that it does not supply report content, and that it only states facts without buy/sell recommendations. That scope-disclosure is genuine behavioral context, though read-only/safety traits and any limits are left implicit.

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 purpose is front-loaded in the first sentence, and the honest-declaration sentences each add a distinct constraint. It is somewhat repetitive and longer than strictly necessary, but no sentence is pure filler.

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?

An output schema exists, so return values need not be explained, and for a one-parameter tool the description covers what it returns, its scope limit, and its intended use. The main residual gap is parameter format guidance, which is minor given the output schema's presence.

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% for the single required 'code' parameter, so the description should compensate. It implies code is used for 代码核对/官方简称 lookup, giving the parameter a purpose, but it never specifies format or accepted values, leaving the agent to infer how to populate it.

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 names a specific output (代码核对/官方简称 + 行情快照) and ties it to a concrete use case (研报精读时的交叉验证), and explicitly disclaims that it does not return research-report content. This lets an agent distinguish it from pure siblings like code_verify or market_snapshot, though the combined 'grounding' framing is a little abstract.

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?

It states context of use ('供研报解读时交叉验证') and a prerequisite (research report text must be pasted by the user), which is useful. However it never explicitly contrasts itself with the sibling tools it overlaps with (code_verify, market_snapshot) or states when NOT to use it, so routing is implied rather than directed.

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