get_shfe_daily

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful behavioral context: accepted date formats, default to current trading day, returns a DataFrame with 11 listed columns, or None if no data for the given date. It does not disclose rate limits or source quirks, but the provided details go beyond the 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 well-organized with a title, source URL, parameter documentation, return description, and field list. Each section earns its place, and the column list is essential because there is no output schema. It is slightly verbose with repeated phrases but not excessive, earning a 4.

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 single-parameter, read-only tool with no output schema, the description fully covers invocation: parameter options and defaults, return type, column names, and the None edge case. The source URL adds transparency. The agent has all needed information to select and call the tool correctly, so completeness is excellent.

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 only shows 'date' as a string with a placeholder default. The description greatly enriches this by explaining accepted formats (YYYY-MM-DD, YYYYMMDD, datetime.date), the actual default (current trading day), and accepted types. This compensates for the 0% schema description coverage. The slight mismatch between the schema default '20220415' and the described default 'current trading day' prevents a 5.

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 opens with '上海期货交易所-日频率-量价数据', clearly indicating it retrieves Shanghai Futures Exchange daily volume-price data. The DataFrame column list further specifies the exact return data. It distinguishes from sibling exchange-specific getters by naming SHFE. However, it lacks an explicit verb like '获取/retrieves', relying on the tool name, so it is not a full 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 SHFE daily data via the title and exchange name, but it does not explicitly state when to choose this tool over alternatives like get_futures_daily or other exchange-specific daily getters. It also does not mention any exclusions or preconditions. Guidance is only implicit, not explicit.

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