get_rank_sum

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context beyond annotations: it discloses that the variety rankings are aggregated from symbol rankings for SHFE/CFFEX and thus not true exchange-wide rankings, and that DCE lacks symbol-level rankings. This data-quality caveat is crucial for correct result interpretation.

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 the purpose, followed by notes, parameter documentation, and a lengthy return column listing. While the return column list is useful given the absence of an output schema, the overall text is verbose and could be more tightly structured without losing essential information.

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?

Given the tool's complexity (aggregating data across five exchanges), two parameters with zero schema coverage, and no output schema, the description provides a solid picture: purpose, data caveats, parameter formats, and return fields. It is nearly complete, though a brief mention of when to prefer this tool over exchange-specific rank functions would complete the guidance.

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%, so the description must compensate. It does so by documenting the date parameter's accepted formats (YYYY-MM-DD, YYYYMMDD, datetime.date) and default behavior (empty = today), and the vars_list format with an example and default (empty = all commodities). This adds substantial meaning beyond the bare schema.

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 collects member position ranking data (top 5/10/15/20) from five futures exchanges. It identifies the specific resource and scope, but does not explicitly distinguish itself from sibling tools like get_rank_sum_daily or exchange-specific rank table functions, so it falls 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 provides important caveats about data availability across exchanges (e.g., SHFE/CFFEX only publish symbol-level rankings, DCE only publishes variety-level rankings), which guides interpretation. However, it offers no guidance on when to choose this tool versus alternatives such as get_rank_sum_daily or per-exchange rank table tools, leaving tool selection to inference.

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