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KitchenSink4AI

io.github.nometalalchemist/kitchensink4xl

by KitchenSink4AI
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Local

clear_filter

Remove an autofilter from a worksheet and unhide the rows it hid. Specify a sheet or use the active filter range; returns the count of unhidden rows.

Instructions

Remove the autofilter from a sheet and unhide the rows it hid, the reverse of set_filter. location or sheet picks the sheet; the sheet's active autofilter range is used when location is omitted. A sheet with no autofilter refuses (NOT_FOUND) rather than silently no-opping. Returns how many rows were unhidden. A hazardous workbook refuses unless allow_loss is true. Auto-backup: prev/anchor slots in .ks4xl-backups; atomic verified save. Refuses while open in Excel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
sheetNo
backupNo
locationNo
allow_lossNo
verify_comNo

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. Changed2 schema fields changedv1.1.0
    • addedInput schema / properties / location / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]
    • removedInput schema / properties / location / title
      Removed value: -"Location"
  3. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false, so the description carries the behavioral burden and exceeds it. It discloses error behavior (NOT_FOUND on no autofilter), return value (rows unhidden), loss protection semantics, auto-backup specifics (prev/anchor slots, atomic verified save), and a concurrency restriction (refuses while open in Excel). This is rich, non-obvious behavior an agent needs to know.

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?

Every sentence carries distinct information: core action, sheet selection, error policy, return value, safety guard, backup mechanism, and lock-out condition. The main purpose is front-loaded, followed by supporting details without fluff or repetition.

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

Completeness5/5

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

For a mutating tool with no output schema and six parameters, the description covers the critical operational aspects: error modes, safety gates, backup behavior, row-count return, and Excel lock. An agent can predict outcomes and avoid dangerous invocations from the description alone.

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 description coverage is 0%, so the description must compensate. It explains location/sheet selection, allow_loss, and implies backup behavior with the auto-backup note, but it does not clarify the exact semantics of the backup boolean or verify_com parameter at all. Since two of six parameters remain ambiguous, the compensation is partial.

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 ('Remove the autofilter from a sheet') plus the concrete side effect ('unhide the rows it hid'). It explicitly frames itself as the reverse of set_filter, which distinguishes it from sibling filtering tools. No ambiguity remains 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 Guidelines4/5

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

The description gives clear operational context: how the sheet is selected, what happens when no autofilter exists, and preconditions like hazardous workbook handling and Excel-open refusal. It names set_filter as the counterpart, implying when this tool is the appropriate choice, though it does not enumerate alternatives or contrast with sibling tools explicitly.

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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