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KitchenSink4AI

io.github.nometalalchemist/kitchensink4xl

by KitchenSink4AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Get Cells

get_cells
Read-only

Fetch many individual cells in one call, labeling results as cached, formula, absent, or value so formulas without cached results aren't mistaken for blanks. Read-only; works on open files.

Instructions

Read many individually addressed cells in one call, the scatter complement to the rectangular read_range. cells is a list of A1 strings or location objects, each resolving to ONE cell (1,000-cell ceiling); values is cached, formula, or both, and every returned value carries the honest label (cached, absent, formula, value), so a formula with no cached value is never passed off as blank. Read-only; works while the file is open in Excel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
cellsYesIndividually addressed cells: A1 strings or location objects, each resolving to ONE cell.
sheetNo
valuesNocached

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 / cells / description
      Added value: +"Individually addressed cells: A1 strings or location objects, each resolving to ONE cell."
    • addedInput schema / properties / cells / items / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "object"
+  }
+]
  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 carry only readOnlyHint=true and openWorldHint=false. The description adds substantial behavioral context beyond these: the values options (cached, formula, both), the honest labeling scheme (cached/absent/formula/value) so a formula without a cached value is never passed off as blank, and that it works while the file is open in Excel. This is rich, non-redundant disclosure.

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?

A single dense paragraph that front-loads purpose and differentiation, then the ceiling, then the values/labeling semantics, then the read-only and open-file behavior. Every clause earns its place; the only minor issue is that it reads as one long run-on sentence, slightly hurting scannability.

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?

For a read-only tool with readOnlyHint=true and no output schema, the description covers the essential call constraints: the 1,000-cell ceiling, values behavior, labeling semantics, and open-file operation. It does not state behavior when the ceiling is exceeded, but the ceiling itself is flagged. The labeling detail partially compensates for the absent output schema.

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?

Schema coverage is only 25% (only 'cells' has a description), so the burden falls on the description. It clarifies the two semantically interesting parameters: 'cells' (A1 strings or location objects, each resolving to one cell, 1,000-cell ceiling) and 'values' (cached, formula, or both). However, 'path' and 'sheet' receive no explanation in either the schema or the description, leaving a gap for the two least-parameterized arguments.

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?

States a specific verb (read) and resource (individually addressed cells) and immediately differentiates itself as the 'scatter complement' to read_range. An agent can distinguish it from the 38 siblings without opening any schema.

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?

Names the alternative (read_range) and the contrasting selection criterion (scatter vs rectangular), and discloses the 1,000-cell ceiling that bounds valid use. It stops short of listing explicit exclusions (e.g., use read_range for contiguous blocks), but the context is clear enough to route correctly.

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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