futures_hold_pos_sina

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds some context beyond annotations: the source URL and that the return is a pandas DataFrame. However, it does not disclose details like data freshness, pagination, or the exact structure of the returned DataFrame. Given annotations cover the key traits, a score of 3 is appropriate.

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 follows a clear docstring structure: title, URL, parameters, and return type. Every line serves a purpose and there is no filler text. It is not front-loaded with a user-focused sentence, but it is concise and easy to scan. A 4 reflects good structure within a minimal space.

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 there is no output schema and the description is the only source of parameter meaning, it provides basic completeness: all three params are explained, and the return type is stated as pandas.DataFrame. However, it lacks details about what columns the DataFrame contains, how '成交持仓' is structured, and how this tool relates to the many sibling futures tools. Without this, an agent might not know if it returns daily historical data, current positions, or something else. This is a moderate completeness level.

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 burden of explaining parameters. It does this well: symbol is given an explicit choice set ({"成交量", "多单持仓", "空单持仓"}), contract is defined as '期货合约', and date as '查询日期'. It also specifies the return type. While date format and contract syntax are not explicitly detailed, the defaults in the schema (e.g., '20240223', 'OI2501') help. This meaningfully compensates for 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 is primarily a noun phrase '新浪财经-期货-成交持仓' (Sina Finance - Futures - Volume/Open Interest) followed by a URL and parameter docs. It identifies the data source and topic but lacks an explicit verb like 'query' or 'fetch'. The return type 'pandas.DataFrame' implies data retrieval, but the action is not stated directly. It does not distinguish itself from sibling tools beyond the source and data type.

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 no guidance on when to use this tool versus alternatives. There are no exclusions, prerequisites, or references to other tools. It only lists parameters and return type, leaving the agent to infer usage context from the tool name and sibling list.

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