get_market_analysis_timeframe

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it's based on current real dates (not training data), returns a formatted string, and should be called first in analysis workflows. However, it doesn't mention potential limitations, error conditions, or whether the timeframe calculation involves any external data fetching or computation costs.

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-structured with clear sections (purpose, usage guidance, parameters, returns) and uses efficient language. Every sentence adds value, though the parameter documentation could be slightly more concise. The formatting with clear headings enhances readability.

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 moderate complexity (single parameter with enum values), no annotations, and the presence of an output schema (implied by the Returns section), the description is quite complete. It covers purpose, usage context, parameter semantics, and return format. The main gap is lack of behavioral details about potential limitations or error handling.

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 description adds significant value beyond the input schema, which has 0% description coverage. It fully documents the single parameter 'period' with all possible enum values ('recent', 'quarter', 'half_year', 'year'), their meanings, and the default value. This completely compensates for the schema's lack of 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 clearly states the tool's purpose: '获取适合市场分析的时间范围' (get suitable timeframe for market analysis) and specifies it's based on current real dates rather than training data. It distinguishes itself from siblings by focusing on timeframe calculation rather than data retrieval, though it doesn't explicitly contrast with specific alternatives.

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 clear context for when to use this tool: '在进行市场分析或大盘分析时首先调用' (should be called first when conducting market or overall market analysis). It establishes a prerequisite role but doesn't explicitly mention when NOT to use it or name specific alternative tools for different scenarios.

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