resolve_date_range

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

No annotations are provided, so the description carries the full behavioral transparency burden. It discloses server-side exact-time computation, consistency benefits, supported expression categories, and the complete return JSON structure including date_range, current_date, and description. It does not cover error cases or timezone behavior, but the key behavioral characteristics an agent needs are present.

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 long but every section earns its place: a clear headline, a rationale, a recommended usage flow, an args section, a returns section, and two end-to-end examples. The structure uses headings and bullet lists to make the content scannable, and the key recommendation is front-loaded.

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 utility tool, the description covers why to use it, how to use it, what expressions are accepted, what the output looks like, and how to chain it with downstream tools. The output schema is effectively documented through the Returns section and examples. Nothing essential for correct invocation is missing.

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 defines expression as type string, so schema coverage is 0% and the description fully compensates. It enumerates supported natural-language categories (single day, week, month, recent N days, dynamic days), gives concrete Chinese and English examples, and shows exactly how the expression translates into the return date_range. This is far beyond basic parameter documentation.

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 a specific verb-resource statement: '将自然语言日期表达式解析为标准日期范围' (parse natural language date expressions into standard date ranges). It further clarifies the tool's role, distinguishes it from direct AI date calculation, and provides examples of the exact output. This makes the tool's purpose unmistakable.

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 explicitly explains when to use the tool: whenever users provide natural language date expressions like '本周' or '最近7天', and gives a recommended call flow before invoking downstream analysis tools. It does not explicitly state when not to use it or name alternative date-handling tools, but the recommended workflow is clear and actionable.

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