resolve_pillarsIdentify candidate Gregorian years matching given four pillars within a specified date range, requiring user confirmation when multiple candidates exist and flagging input errors if none found.
用户只给出生四柱、不给出生日期时，反查符合这四个干支的候选公历年份。四柱会重复，没有唯一候选就不能继续完整推演；0 个候选说明输入有误，多个候选必须让用户确认。
| Name | Required | Description | Default |
|---|---|---|---|
| pillars | Yes | ||
| end_year | Yes | ||
| start_year | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It does this well by explaining that pillars repeat, that no unique candidate blocks further reasoning, that zero candidates implies invalid input, and that multiple candidates must be confirmed by the user. This is substantive behavioral context beyond a simple operation statement.
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, front-loaded with the core use case, and every sentence adds value—use case, repeat behavior, failure interpretation, and user-confirmation requirement. There is no wasted text.
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?
The description covers the core workflow and ambiguous-result handling well, and an output schema exists to describe return values. However, the tool has three required parameters with no schema descriptions and no mention of pillar syntax or year-range semantics, leaving an agent to guess important input details.
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 0%, so the description must compensate for missing parameter meaning. It clarifies that pillars refer to four ganzhi and that the tool returns candidates, but it does not explain the format of the pillars string or the semantics/range of start_year and end_year. This is a meaningful gap for correct invocation.
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 a specific action: reverse-look up candidate Gregorian years matching the user's provided four pillars, and it specifies the exact scenario in which this tool is used. It does not explicitly differentiate from sibling tools, but the described operation is distinctive enough that confusion is unlikely.
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 explicitly says when to use the tool: when the user gives only four pillars and not a birth date. It provides clear context and behavioral expectations, though it does not mention alternatives or an explicit 'do not use when...' condition.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.