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KitchenSink4AI

io.github.nometalalchemist/kitchensink4xl

by KitchenSink4AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Create Table

create_table

Turn a worksheet range into a named Excel table with headers, styling, banding, and optional totals, while blocking conflicting names and overlapping tables and backing up the workbook.

Instructions

Turn a range into an Excel table (ListObject) named name. With header true the first row supplies the column names (deduplicated); style is a built-in style; row_stripes and col_stripes toggle banding. totals maps columns to a function (sum, average, count, min, max...). Refuses an overlap with an existing table, and a name already taken by a table or defined name. Hazardous workbooks refuse unless allow_loss is true. Auto-backup to .ks4xl-backups; atomic verified save. Refuses while open in Excel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
pathYes
sheetNo
styleNoTableStyleMedium9
backupNo
headerNo
totalsNo
locationYes
allow_lossNo
totals_rowNo
verify_comNo
col_stripesNo
row_stripesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changedv1.1.0
    • addedInput schema / properties / location / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "object"
+  }
+]
  3. First observedv1.0.0

TDQS

A3.7/5.0
Behavior5/5

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

Annotations only provide readOnlyHint=false and destructiveHint=false, which is minimal. The description compensates fully by disclosing key behaviors: refuses overlap with existing tables, rejects duplicate names (tables or defined names), requires allow_loss for hazardous workbooks, performs auto-backup with atomic verified save, and refuses while the workbook is open in Excel. This is rich, actionable context beyond any structured field.

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 a single dense paragraph that front-loads the core action and then lists options with inline explanations. It is concise without being telegraphic, and each sentence adds distinct information. Minor inefficiency: the phrase 'named name' is slightly awkward, and the backup/atomic save sentence could be separated for readability, but overall it is well-structured.

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

Completeness2/5

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

Given 13 parameters, no output schema, and complex behavior, the description is incomplete. It does not mention what the tool returns (e.g., success message, table object), nor does it define how location (string vs object) should be specified, or the meaning of totals_row and verify_com. For a complex mutation tool with zero schema coverage, an agent would need additional investigation to call it correctly.

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?

Schema coverage is 0%, so the description must explain parameters. It does explain header, style, row_stripes, col_stripes, totals (with example functions), allow_loss, and backup (via auto-backup mention). However, it leaves path, sheet, location, totals_row, and verify_com undefined. For a 13-parameter tool, this partial coverage is adequate but not thorough – it adds meaning for roughly half the parameters.

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 opens with a specific verb and resource: 'Turn a range into an Excel table (ListObject) named name.' This clearly distinguishes the tool's action from siblings like get_table (retrieve) or write_range (write values), and the qualifier 'ListObject' adds precision. There is no ambiguity about what the tool does.

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

Usage Guidelines2/5

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

The description does not state when to use this tool versus alternatives. It never mentions sibling tools like get_table for reading tables or write_range for writing raw data, nor does it provide conditions for selection. The only 'when' hints are behavioral refusals (e.g., overlap, name conflicts), not usage context. This leaves an agent without explicit routing guidance.

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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