futures_rule

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

Annotations already declare this as a read-only, idempotent, non-destructive operation. The description adds the recent-date constraint and the source URL, which is useful. However, it does not describe what exactly the returned DataFrame contains (columns, row count, or behavior for invalid dates), leaving some behavioral ambiguity.

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 concise, with a structured docstring including param, type, return, and rtype. The title is repeated in the first line, which is slightly redundant, but overall it is compact and readable for an agent.

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?

For a simple one-parameter data retrieval tool with good annotations, the description covers the source, parameter constraint, and return type. It lacks specifics about the DataFrame schema and error handling, but given the tool's simplicity, it is reasonably complete.

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?

The schema provides only a string parameter with a default, and description coverage is 0%. The description compensates by stating the date must be a trading day and recent, narrowing down valid values. It stops short of specifying the exact format (e.g., YYYYMMDD) explicitly, but the default value implies 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 identifies the tool as a trading calendar data table from Guotai Junan Futures, which clearly indicates the resource. However, it lacks an explicit verb like 'fetch' or 'retrieve,' and the name 'futures_rule' is ambiguous until the title is read. It distinguishes from siblings by the specific calendar data scope, but not strongly.

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?

The docstring provides a key usage constraint: the date must be a trading day and recent. This guides the agent on valid input, but there is no mention of when to use this tool over other futures-data siblings, nor any exclusion criteria. It implies usage context without explicit alternatives.

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