futures_global_hist_em

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so safety profile is covered. The description adds that the return is a pandas.DataFrame and that symbol codes can be discovered via another function, but does not detail column names, date ranges, or pagination behavior. No contradictions with annotations.

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 compact and well-structured, starting with a clear title line and source URL, followed by parameter/return documentation. Every sentence contributes useful information, though the URL example could be integrated more elegantly.

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 no output schema, the description should explain return values. It identifies the return as historical market data and a DataFrame, but lacks specifics on columns, date range, or data granularity. The annotations cover risk characteristics, so overall completeness is adequate for a simple one-parameter tool but with clear gaps.

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 coverage is 0%, so the description must compensate. It explains that 'symbol' is a product code and points to futures_global_spot_em for obtaining all valid codes. This adds meaning beyond the schema's bare default value, but it does not explain the format (e.g., what 'HG00Y' represents or how it maps to the URL example).

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 retrieves historical market data for international futures from Eastmoney, with a specific source URL and data type (pandas.DataFrame). It distinguishes itself as 'international futures' history, which helps separate it from domestic futures tools, though it does not explicitly name sibling alternatives.

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 description provides a concrete method to obtain valid symbol values by referencing ak.futures_global_spot_em(), giving implicit guidance on when to use this tool (when you need historical data for international futures). However, it does not explicitly state when not to use it or compare to alternative futures history tools.

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