analyze_and_predict

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

No annotations are provided, so the description carries the full burden. It mentions analyzing historical data and generating reference numbers, but does not indicate side effects or safety (e.g., read-only, destructive). The 'for reference only' note adds some transparency about reliability, but behavioral details are sparse.

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 a single sentence in Chinese, concise and front-loaded with the action. No wasted words or redundant information.

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 no parameters, no output schema, and no annotations, the description is minimal. It explains what it does (generates 10 sets based on frequency), but does not describe output format, number range, or algorithm details. Sufficient for a simple tool, but could be more complete.

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 input schema has zero parameters, so schema_description_coverage is 100%. The description does not need to add parameter details. With 0 params, baseline is 4, and the description does not detract.

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 verb (analyze and generate) and the resources (historical data of Double Color Ball, 10 sets of reference numbers). It distinguishes from sibling tools like get_all_lottery_history (which retrieves raw data) and calculate_ac_value (which computes a specific metric).

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 mentions the output is for reference only, which is a caveat, but does not explicitly state when to use this tool versus alternatives like get_all_lottery_history or get_latest_lottery. No guidance on prerequisites or exclusions.

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