Export game numeric tables as Lua record arrays or JSON text, with optional column filtering to reduce size. Rejects outputs over 1MB to guide narrowing.
导出当前工作区的数值表为 lua record 数组模块（return { [1] = { Key = v, ... } }）或 JSON 数组文本（format 缺省 lua）。中文列名自动转 ["列名"] 字符串键；columns 可选收窄导出列。产物超 1MB 拒绝并引导收窄。先 list_tables 拿表名。
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes | 表名（来自 list_tables） | |
| format | No | 导出格式（缺省 lua） | |
| columns | No | 导出列子集（可选；大表收窄产物） |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses the precise output structure, the automatic conversion of Chinese column names to string keys, the optional column narrowing behavior, and the over-1MB rejection path. This gives the agent a detailed picture of what invoking the tool entails.
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 with the primary action and output format, followed by key options, size-limit behavior, and prerequisite. There is no redundant or filler 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?
For a three-parameter tool with no output schema, the description covers output shape, default format, column-name handling, size-limit rejection, and how to obtain the required table parameter. An agent has enough information to call it correctly.
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 parameter descriptions already document table, format, and columns. The tool description mostly restates these facts and adds no novel parameter-level semantics beyond what the schema provides.
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 exports the current workspace's table as a Lua record array module or JSON array text, naming the exact output formats. It implies distinction from read_table by focusing on serialized output, but it does not explicitly contrast itself with any sibling tool.
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?
It provides clear usage context: get the table name from list_tables first, use the columns parameter to narrow large exports, and expect rejection with guidance when output exceeds 1MB. It does not state when to prefer this over alternatives or explicitly list exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.