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read_full_content

Reads entire Excel workbook including all text data and embedded images. Returns structured sheet data and extracted images with cell positions for comprehensive document analysis.

Instructions

Read the FULL content of an Excel file including all text data AND embedded images.

This is the primary tool for comprehensive document analysis. Returns all sheet data as structured text followed by all extracted images with their cell positions. Ideal for analyzing documents where both text and diagrams/screenshots are essential, such as requirement definitions, reports, or design specs.

For very large files, data is paginated per sheet. Image extraction uses dual strategy (cell-mapping + archive) for maximum coverage. Cell text carries formatting markers ([B]=bold, [S]=strikethrough, [HL:color]= highlight) so emphasis and status marks survive into the analysis.

Hidden rows/columns are skipped by default, except hidden cells that visible formulas depend on.

@param file_path: Absolute path to the .xlsx file. @param max_rows_per_sheet: Max rows to read per sheet (default 500). @param max_image_width: Max width for image optimization (default 1024). @param max_image_height: Max height for image optimization (default 1024). @param include_hidden: Set true to also read hidden rows/columns. @return: Mixed list of TextContent and ImageContent covering entire workbook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
include_hiddenNo
max_image_widthNo
max_image_heightNo
max_rows_per_sheetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses key behaviors: pagination per sheet, dual-strategy image extraction, formatting markers, and hidden row/column handling. No annotations provided, so description carries full burden and adds significant value.

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?

Well-structured with front-loaded purpose, usage context, behavioral details, and parameter documentation. Each sentence adds value, though slightly lengthy.

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?

Covers purpose, usage, behaviors, parameters, and output format (TextContent/ImageContent) with an existing output schema. Complete for the tool's complexity.

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 fully explains all parameters with defaults and usage details (e.g., 'Absolute path', 'Max rows to read per sheet'). Compensates completely.

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?

Clearly states 'Read the FULL content of an Excel file including all text data AND embedded images'. Distinguishes from siblings like 'read_excel_data' and 'extract_images' by emphasizing comprehensiveness and combined text-image output.

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?

Explicitly describes ideal use cases (requirement definitions, reports, design specs) and notes pagination for large files. Lacks explicit when-not-to-use or alternatives, but strong context implies scope.

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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