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vlookup_helper

Read-only

Perform cross-file lookups by matching keys between two Excel workbooks and returning specified columns, with optional fuzzy matching for approximate matches.

Instructions

Perform cross-file lookup akin to VLOOKUP with optional fuzzy matching.

Args: lookup_file: Workbook containing keys to look up. data_file: Workbook containing reference data. lookup_column: Column in lookup_file to match. data_key_column: Column in data_file to join on. data_return_columns: Columns from data_file to return. lookup_sheet, data_sheet: Sheet names. fuzzy: If True, perform fuzzy matching. fuzzy_threshold: Threshold for fuzzy confidence. output_file: Optional path to write augmented lookup results. header_row: 1-based header row index.

Returns: dict: Mapping rows to matched results and match scores.

Notes: - Read-only on inputs unless output_file is provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fuzzyNo
data_fileYes
data_sheetNoSheet1
header_rowNo
lookup_fileYes
output_fileNo
lookup_sheetNoSheet1
lookup_columnYes
data_key_columnYes
fuzzy_thresholdNo
data_return_columnsYes
Behavior5/5

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

The Notes section discloses that inputs are read-only unless output_file is provided, refining the readOnlyHint annotation. It also describes the return value as a dict mapping rows to matched results and match scores, adding useful 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.

Conciseness5/5

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

The description uses a clear docstring structure (summary, Args, Returns, Notes) and is appropriately sized for the tool's complexity. Every section provides necessary information without redundancy.

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 tool with 11 parameters, no output schema, and only a readOnlyHint annotation, the description is comprehensive: it explains all parameters, the return format, and the conditional write behavior, making it fully actionable for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description's Args section lists all 11 parameters with concise explanations (e.g., 'lookup_file: Workbook containing keys to look up'), fully compensating for the lack of schema-level descriptions.

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 'Perform cross-file lookup akin to VLOOKUP with optional fuzzy matching,' which is a specific verb+resource (cross-file lookup) and distinguishes it from similar siblings like merge_datasets by referencing VLOOKUP semantics.

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 phrase 'akin to VLOOKUP' provides clear context for when to use this tool, implying a lookup/join operation. However, it does not explicitly mention alternatives or exclusions, which would merit a 5.

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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