get_adjust_factor

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

No annotations are present. The description only lists output fields and does not disclose behavior such as error handling, data range limitations, or read-only nature. The agent has little insight into what happens during invocation.

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 very short and to the point, with one sentence and a field list. It could be improved by adding usage context, but it avoids fluff.

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?

With 3 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the date range parameters, the required code parameter, or the structure of the output beyond field names.

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%, and the description does not explain the input parameters (code, start_date, end_date). It only documents output fields, leaving the agent to infer parameter meanings from names alone.

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 it provides price adjustment factors and lists the fields. It mentions the algorithm source (baostock) which adds specificity. However, it does not differentiate from sibling tools like get_history_k_data or get_dividend_data, which also involve stock data.

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, no prerequisites, and no exclusions. The description simply states what it does without context for usage.

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