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write_cells

Write values to Excel cells or ranges in live workbooks or .xlsx files without needing Excel installed. Supports single values, arrays, or 2D arrays while preserving existing content.

Instructions

Write values to a cell or range. Use "workbook" for live Excel, or "path" for a .xlsx file on disk (no Excel needed, preserves images/charts). Accepts a single value, a flat array, or a 2D array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workbookNoOpen workbook name (live Excel)
pathNoFile path to .xlsx (no Excel needed)
rangeYesCell range (e.g. "A1" or "A1:B5")
valueYesValue(s) to write
sheetNoSheet name (default: active sheet)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that using 'path' preserves images/charts, which adds useful context beyond basic writing. However, it lacks details on permissions, error handling, or side effects like overwriting existing data, leaving gaps in transparency for a mutation tool.

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 front-loaded with the core purpose and efficiently explains key usage details in two sentences. Every sentence adds necessary information without redundancy, making it appropriately sized and easy to parse.

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?

Given the tool's complexity as a mutation tool with no annotations and no output schema, the description is somewhat complete but has gaps. It covers purpose and parameter usage well but lacks details on behavioral aspects like error conditions or return values, which are important for safe invocation.

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 description coverage is 100%, so the baseline is 3. The description adds value by clarifying the semantics of 'workbook' vs. 'path' for different use cases and specifying acceptable value types (single, flat array, 2D array), which enhances understanding beyond the schema's technical definitions.

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 the action ('Write values') and the resource ('to a cell or range'), specifying the tool's function. It distinguishes from siblings like 'read_cells' by focusing on writing, and from 'format_cells' by handling data input rather than styling, making the purpose specific and well-differentiated.

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 provides clear context on when to use this tool by explaining the choice between 'workbook' for live Excel and 'path' for file-based operations, which helps in selecting the appropriate parameter. However, it does not explicitly state when not to use it or name alternatives like 'execute_vba' for more complex tasks, leaving some guidance implicit.

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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