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 PRO requirement and 403 error, and specifies the return format as a JSON array with fields. However, it does not mention pagination, rate limits, or error handling beyond the 403 case, leaving some behavioral traits undisclosed.

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 description is well-structured and front-loaded with purpose and requirement, followed by args and returns. It is concise and avoids unnecessary prose, though the argument list duplicates schema descriptions, which is a minor redundancy.

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 description includes purpose, parameters, return fields, and authentication requirement, covering essential details. It lacks guidance on edge cases (e.g., invalid symbol handling, date range validation) and does not explain the meaning of the adjustment factor metric, leaving gaps for less familiar users.

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 descriptions cover all four parameters at 100% coverage, so the description adds no incremental semantic value by repeating them. The trade_date exclusivity note is already present in the schema, meaning the description is redundant but not harmful, fitting the baseline of 3.

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 clearly states the tool returns adjustment factors (复权因子) for market data, with concrete examples like 000001.SZ. It does not explicitly differentiate from the sibling `etf_adj_factor`, but the name and example imply stock context, which is a minor gap.

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?

No guidance is provided on when to use this tool versus alternatives like `etf_adj_factor` or `daily`. The only usage-related note is the PRO plan requirement and 403 error for lower tiers, which is a licensing constraint rather than contextual selection guidance.

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