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u9401066

asset-aware-mcp

by u9401066

plan_table

Design table schemas from questions, list templates, or create tables from template options.

Instructions

📋 表格規劃工具:Schema 設計、模板查詢、模板建表。

Operations:

  • schema: 根據問題自動規劃表格結構

  • templates: 列出內建表格模板

  • from_template: 從模板快速建立表格

Args: operation: 操作類型 question: [schema] 使用者問題 doc_ids: [schema] 相關文件 ID hints: [schema] 結構提示 template_name: [from_template] 模板名稱 title_override: [from_template] 自訂標題

Examples: plan_table("schema", question="比較三種藥物副作用") plan_table("templates") plan_table("from_template", template_name="drug_comparison")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationYes
questionNo
doc_idsNo
hintsNo
template_nameNo
title_overrideNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions operations like '建表' (create table) which might imply side effects, but the tool name 'plan_table' suggests planning only. There is no clarification on whether operations are read-only or destructive, nor any authentication or rate limit information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections, bullet points, and emojis, making it easy to scan. It front-loads the tool's purpose. It is fairly concise, though it could potentially be more compact without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, 3 sub-operations) and lack of annotations, the description explains the operations and parameters but lacks details on expected output, error handling, or behavioral nuances. The presence of an output schema partially mitigates the need for return value descriptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds some meaning by mapping parameters to operations (e.g., '[schema] 使用者問題') and providing examples. However, the descriptions are very terse and do not explain parameter formats, constraints, or behaviors, leaving much to be inferred.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool as a table planning tool with three operations (schema, templates, from_template), which specifies the verb and resource. However, it does not explicitly differentiate from sibling tools like docx_table_edit_plan or table_draft, which also deal with table planning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides examples for each operation, which implicitly suggests when to use each sub-operation. However, there is no explicit guidance on when to use this tool versus alternative tools, nor are there any conditions or exclusions mentioned.

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

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