get_rank_sum_daily

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

The description adds substantial behavioral context beyond the annotations: it explains that SHFE and CFFEX variety rankings are aggregated from contract rankings and thus not true rankings, that DCE lacks contract rankings, and it details default date and commodity behavior. These caveats are critical for correctly interpreting the data and go well beyond the readOnly/idempotent hints.

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 front-loaded with its purpose, followed by critical caveats, parameter documentation, and a return schema. It is somewhat lengthy but each section serves a purpose, and the docstring-style format is standard and scannable. It earns a 4 rather than 5 because the return schema section is truncated and includes unnecessary duplication of column types.

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 covers the core caveats, parameter semantics, and a partial return schema. However, it does not list all expected output columns (it stops at vol_top10, missing top15/top20 columns), does not explicitly name all four exchanges, and lacks error/empty-data behavior. Given the tool's complexity and absent output schema, this is a minor but notable gap.

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 carries the full burden of parameter semantics. It defines start_day and end_day formats (YYYY-MM-DD, YYYYMMDD, datetime.date), defaults to today when empty, and describes vars_list as a list of contract varieties with example ['RB','AL'], defaulting to all commodities when empty. This fully compensates for the schema's lack of descriptions.

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 collects top 5/10/15/20 member position ranking data from four futures exchanges, with specific notes about aggregation rules. However, it does not differentiate from sibling tools like get_rank_sum or futures_dce_position_rank, so it stops short of a 5.

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 implies usage for daily futures position ranking queries by describing what data it returns, but it provides no explicit guidance on when to choose this tool over alternatives, nor any exclusions. The notes about data aggregation are more about interpretation than tool selection, so the guidance is only implicit.

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