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u9401066

asset-aware-mcp

by u9401066

table_draft

Create, update, and add rows to table drafts with automatic save and resume. Commit drafts to final tables when complete.

Instructions

📝 草稿工作流:建立、更新、新增資料、恢復、提交。

草稿會自動保存,即使對話中斷也能恢復。 適合長時間的表格建立流程。

Operations:

  • create: 建立草稿

  • update: 更新草稿

  • add_rows: 批次新增資料到草稿

  • resume: 恢復草稿(Token-efficient)

  • commit: 草稿轉正式表格

  • list: 列出草稿

  • delete: 刪除草稿

Args: operation: 操作類型 draft_id: [大部分操作] 草稿 ID title: [create/update] 標題 intent: [create/update] comparison / citation / summary proposed_columns: [create/update] 欄位定義 extraction_plan: [create/update] 抽取計畫 source_doc_ids: [create/update] 來源文件 ID source_sections: [create/update] 來源章節 ID notes: [create/update] 工作筆記 rows: [add_rows] 資料列

Examples: table_draft("create", title="Drug Comparison", intent="comparison", proposed_columns=[{"name":"Drug","type":"text"}]) table_draft("add_rows", draft_id="draft_xxx", rows=[{"Drug":"A"}]) table_draft("commit", draft_id="draft_xxx")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationYes
draft_idNo
titleNo
intentNo
proposed_columnsNo
extraction_planNo
source_doc_idsNo
source_sectionsNo
notesNo
rowsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Discloses auto-save and resume after interruption. However, with no annotations, it lacks details on destructive consequences (e.g., delete), authentication needs, or rate limits. Moderate transparency.

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?

Well-structured with sections, emoji, bullet list, and examples. Not overly verbose but could be slightly more concise. Overall effective.

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

Completeness4/5

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

Given 10 parameters and operation variants, the description covers all parameter uses, provides examples, and mentions auto-save. Output schema exists but is not described; still, the description is fairly complete for a draft tool.

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

Parameters4/5

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

With 0% schema description coverage, the description adds significant value by explaining each parameter's purpose per operation (e.g., draft_id, rows). Provides clarity beyond the schema.

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

Purpose5/5

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

The description clearly states it is a draft workflow for tables, listing all operations (create, update, add_rows, resume, commit, list, delete). It distinguishes from sibling tools like table_manage by focusing on the draft lifecycle.

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

Usage Guidelines4/5

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

Explicitly mentions suitability for long table creation processes and auto-save/resume. Provides operation-specific parameter documentation and examples, but does not explicitly state when not to use or list alternatives.

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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