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

With no annotations, the description carries the full burden and does well: it discloses the data's provenance ('唯一用时间积累的资产…LLM 无法生成') and what the record contains, which tells the agent this is a historical, non-synthesizable read. It does not explicitly confirm read-only/no side effects or mention pagination/limits, so it stops just short of complete.

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?

It is front-loaded with what the tool returns, then usage, then alternatives, with no redundant restatement of the name. The middle sentence about the time-accumulated asset is slightly editorial but earns its place by differentiating this tool's data from LLM-generated output.

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?

There is no output schema, so the description must explain return values, which it does concretely (hit rate, verified/pending stats, per-signal predicted_on→verify_by results). Combined with the routing guidance and complete parameter coverage, an agent has everything needed to call and interpret it.

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 100% and both parameters (industry, include_signals) are already documented in the schema, including defaults. The description alludes to industry hit-rate filtering but adds no syntax, format, or behavior beyond what the schema states, so the baseline 3 applies.

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 states a specific verb and resource (读取信号验证记录) and enumerates exactly what is returned: 命中率, 已验证/待验证统计, and per-signal results from predicted_on to verify_by. It explicitly names the sibling tools it is not (read_signal_board, ask_edge, read_earnings_tracker), so an agent can distinguish it without opening any schema.

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 gives explicit 'Use when' triggers (评估信号板可信度、查某行业历史命中率、复盘已兑现/落空案例) and an explicit 'Use instead' block routing three distinct sibling tools to their own use cases. This is textbook when/when-not/alternative guidance.

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