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YangLang116

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by YangLang116

resolve_date_range

Parses natural language date expressions like 'this week' into precise date ranges for consistent data analysis across tools.

Instructions

【推荐优先调用】将自然语言日期表达式解析为标准日期范围

为什么需要这个工具? 用户经常使用"本周"、"最近7天"等自然语言表达日期,但 AI 模型自己计算日期 可能导致不一致的结果。此工具在服务器端使用精确的当前时间计算,确保所有 AI 模型获得一致的日期范围。

推荐使用流程:

  1. 用户说"分析AI本周的情感倾向"

  2. AI 调用 resolve_date_range("本周") → 获取精确日期范围

  3. AI 调用 analyze_sentiment(topic="ai", date_range=上一步返回的date_range)

Args: expression: 自然语言日期表达式,支持: - 单日: "今天", "昨天", "today", "yesterday" - 周: "本周", "上周", "this week", "last week" - 月: "本月", "上月", "this month", "last month" - 最近N天: "最近7天", "最近30天", "last 7 days", "last 30 days" - 动态: "最近5天", "last 10 days"(任意天数)

Returns: JSON格式的日期范围,可直接用于其他工具的 date_range 参数: { "success": true, "expression": "本周", "date_range": { "start": "2025-11-18", "end": "2025-11-26" }, "current_date": "2025-11-26", "description": "本周(周一到周日,11-18 至 11-26)" }

Examples: 用户:"分析AI本周的情感倾向" AI调用步骤: 1. resolve_date_range("本周") → {"date_range": {"start": "2025-11-18", "end": "2025-11-26"}, ...} 2. analyze_sentiment(topic="ai", date_range={"start": "2025-11-18", "end": "2025-11-26"})

用户:"看看最近7天的特斯拉新闻"
AI调用步骤:
1. resolve_date_range("最近7天")
   → {"date_range": {"start": "2025-11-20", "end": "2025-11-26"}, ...}
2. search_news(query="特斯拉", date_range={"start": "2025-11-20", "end": "2025-11-26"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full responsibility. It discloses server-side time computation, supported expression types, and return format. It does not mention error handling for unsupported expressions or edge cases, but overall it is transparent about its behavior and output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with headings, bullet points, and examples, making it easy to read. However, it is somewhat verbose; the 'Why need' and usage flow sections could be slightly condensed without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter), the description covers everything: purpose, parameter details, return format with example, recommended usage with other tools, and output schema (inferred from Returns section). It is fully sufficient for correct tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'expression' has no schema description, but the description provides extensive documentation: supported expression categories (single day, week, month, last N days), examples, and format. This adds significant meaning beyond the bare schema definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states that the tool resolves natural language date expressions to standard date ranges. It distinguishes from sibling tools by its unique function and provides specific use cases for date conversion, which is not covered by any other tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly recommends the tool as the first call in a workflow, provides a step-by-step usage flow, and explains why it is needed for consistency across different AI models. Examples illustrate when and how to use it with other tools like analyze_sentiment and search_news.

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

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