八字排盘 + AI 深度解读（组合）

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

With no annotations, the description carries the full burden of behavioral disclosure. It discloses the paid nature ('合计 3元/次，账户余额扣费'), the two-step internal workflow, account requirements, and the contents of the returned analysis (大运流年/五行喜忌/事业感情财运). It does not mention potential side effects like record saving or runtime failures, but the key behavioral traits are well covered.

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 compact and front-loaded, starting with the trigger condition and the tool's primary purpose. Each sentence conveys essential information: workflow, cost, prerequisites, and output scope. While not as short as a two-sentence description, it avoids redundancy and remains readable despite covering multiple aspects.

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 complex tool with 10 parameters and no output schema, the description is fairly complete: it explains the combined pipeline, cost, account prerequisites, and high-level output contents. However, it does not describe the response structure or error cases, and it omits practical hints about optional parameters like gender or hour_unknown, leaving the agent to infer their relevance from the schema alone.

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 already provides 100% coverage with descriptions for all 10 parameters. The description adds only marginal context, such as '农历传 lunar=true' which reiterates the schema's existing description ('true=输入为农历'). No additional meaning about parameter formatting, defaults, or interdependencies (e.g., leap/month) is given. The schema does the heavy lifting, so a baseline score of 3 is appropriate.

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 performs a combined BaZi chart calculation and AI deep analysis in one call ('一次调用自动完成①免费排盘→②AI深度解读'). It explicitly lists the resource (八字排盘 + AI 深度解读) and distinguishes it from sibling tools by framing it as the preferred option when users want comprehensive analysis (命盘/运势/事业/感情/财运/婚姻/健康). The verb '自动完成' and scope are specific and unambiguous.

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 when-to-use guidance: '当用户提到出生日期...并希望看命盘/运势/事业/感情/财运/婚姻/健康等分析时，优先调用本工具'. It also mentions prerequisites (server-side account configuration) and cost. However, it does not explicitly exclude use cases like when only a chart is needed (bazi_paipan) or only an AI reading is requested (bazi_ai_reading), so it lacks explicit when-not-to-use guidance.

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