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logisky

logisheets-mcp

by logisky

save_workbook

Exports the spreadsheet to a genuine .xlsx file, optionally rewriting block references as A1 formulas so Excel recalculates without #NAME? errors.

Instructions

Write the workbook to a real .xlsx file the human can open in Excel. This is how you hand your work back — do it when the task is done.

Defaults to the path it was opened from, or last saved to; pass path to write somewhere else. Values, formulas and the block structure are all saved.

IMPORTANT — if the human is going to work on this in Excel, pass resolve_block_refs: true. Formulas that read blocks are written as BLOCKREF/BLOCKREFS, which only LogiSheets understands: Excel shows the saved numbers but turns those cells into #NAME? the moment it recalculates. Resolving rewrites them as ordinary A1 references so Excel can recompute the model. Leave it off when the file is coming back here — the named form is readable and survives rows moving.

The result carries a link to the workbook rather than its bytes, so the host can offer the human the file without any of it passing through your context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoDestination .xlsx path. Defaults to the path the workbook was opened from.
resolve_block_refsNoRewrite BLOCKREF/BLOCKREFS as ordinary A1 references. Set this when the human will open the file in Excel; Excel has no BLOCKREF function and would show #NAME? on recalculation. One-way: a resolved file is an export, not a round trip.
Behavior5/5

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

Despite annotations being minimal, the description extensively discloses behavior: default path (opened from or last saved), what is saved (values, formulas, block structure), the BLOCKREF issue and one-way resolution, and the result carrying a link instead of bytes. This goes far beyond the annotations and provides critical behavioral context.

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 somewhat long but well-structured: purpose first, then defaults, then a critical warning about block refs, and result behavior. Every sentence contributes necessary information, but the length could be trimmed if some details were in schema or annotations. No wasted words, but not maximally concise.

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 save operation with no output schema, the description covers all important aspects: destination, what data is persisted, Excel compatibility nuances, one-way export, and return format (link). It also implies the tool's role in the overall workflow. This is comprehensive for its complexity.

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 100% with both parameters described, but the description adds meaningful context: path defaults and when to set resolve_block_refs (Excel vs round-trip, one-way nature). This goes beyond the schema, so it earns above the baseline 3, though it doesn't introduce new parameter syntax.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool writes a workbook to a real .xlsx file for the human to open. It distinguishes from sibling tools by emphasizing 'real .xlsx file' and 'hand your work back', but does not explicitly differentiate from export_xlsx, so it lacks explicit sibling differentiation. Thus, it's clear but not fully distinguishing.

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?

It explicitly states when to use the tool ('do it when the task is done') and provides detailed guidance on when to set resolve_block_refs (for Excel vs round-trip). However, it does not mention when not to use it or alternatives like export_xlsx, so it lacks exclusions. This is clear context but with no explicit alternatives.

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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