Skip to main content
Glama
KitchenSink4AI

io.github.nometalalchemist/kitchensink4xl

by KitchenSink4AI
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Local

create_table

Create an Excel table from a range: set headers, styles, row/column stripes, and totals. Prevent overlaps and name conflicts, with automatic backup and safety checks for hazardous files.

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

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint=false annotation, the description discloses refusal conditions (overlap, name conflicts, hazardous workbooks, file open in Excel), the behavior of allow_loss, auto-backup to .ks4xl-backups, and atomic verified saving. This is substantial behavioral context that meaningfully goes beyond the annotation.

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

Conciseness5/5

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

The description is compact and front-loaded with the core purpose, followed by dense but relevant behavioral details. Every sentence adds information about how the tool behaves or what the agent must account for. There is no filler or redundancy.

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?

The description provides rich safety and behavior context, but given no output schema, only a single annotation, and 0% schema coverage over 13 parameters, it is not fully complete. An agent still lacks clear semantics for locating the target range/file and for return/verification outcomes. It is above average but not exhaustive enough for a high score.

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 carries a heavy burden. It explains header deduplication, style, row/col stripes, totals mapping, backup, and allow_loss. However, it leaves several important parameters undocumented: path, sheet, location, totals_row, and verify_com. The compensation is good but incomplete for a 13-parameter tool.

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.' It clearly distinguishes this from siblings by focusing on table creation rather than generic write/format operations. The scope is unambiguous and actionable.

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 implies when to use the tool: when a range should become a structured Excel table with styling, totals, and safety guarantees. However, it does not explicitly contrast it with alternatives like write_range or format_cells, nor does it state when not to use it. The usage context is discernible but not explicit.

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

Install Server

Other Tools