analyze_seq_numbers

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the sliding window approach and that it returns theoretical vs. measured values, which adds some context. However, it doesn't describe what the output looks like, whether this is a read-only analysis or has side effects, performance characteristics, or error conditions. For a statistical analysis tool with 3 parameters, this leaves significant behavioral gaps.

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 extremely concise - just one sentence in Chinese that efficiently states the core functionality. It's front-loaded with the main purpose and doesn't waste words. However, the brevity comes at the cost of completeness, as noted in other dimensions. Every word earns its place, but more content might be needed for full understanding.

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 complexity of statistical analysis with 3 parameters, no annotations, and no output schema, the description is incomplete. While it states what the tool does at a high level, it doesn't explain the significance of the analysis, what 'theoretical vs. measured values' means in practice, or how to interpret results. For a tool that presumably returns complex statistical data, this leaves the agent with insufficient context to use it effectively.

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 description coverage is 100%, so the schema already documents all three parameters thoroughly with descriptions, enums, defaults, and constraints. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions '滑窗' (sliding window) which relates to the 'sequence_length' parameter concept, but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.

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: analyzing sequential number occurrence probability using sliding windows and returning theoretical vs. measured values. It specifies the verb ('分析' - analyze) and resource ('号码连续出现概率' - sequential number occurrence probability), making it distinct from siblings like 'analyze_numbers' or 'predict_lottery'. However, it doesn't explicitly differentiate from 'backtest_lottery' which might involve similar statistical analysis.

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. It doesn't mention when this analysis is appropriate, what problems it solves, or how it differs from sibling tools like 'analyze_numbers' or 'backtest_lottery'. The agent receives no contextual usage instructions beyond the basic purpose statement.

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