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read_full_content

Extracts all text data and embedded images from Excel files for comprehensive document analysis. Returns structured sheet content and images with cell positions.

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.

@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). @return: Mixed list of TextContent and ImageContent covering entire workbook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
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?

With no annotations, the description carries full burden. It discloses pagination for large files, dual-strategy image extraction, and return type (mixed list of TextContent and ImageContent). Missing details on permissions, error handling, or performance impact, but still substantial.

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 well-structured into three clear paragraphs plus a param list. Each sentence adds value: purpose, usage context, additional behavior details. No redundancy or fluff, appropriate length.

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?

Given the tool's complexity (4 params, no annotations, output schema exists), the description covers key aspects: purpose, param semantics, pagination, extraction strategy, and return type. Could mention error handling or supported formats, but overall complete enough.

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 includes @param lines explaining each parameter: file_path (absolute path), max_rows_per_sheet (max rows, default 500), and image dimension parameters for optimization. This adds significant meaning beyond the schema's type/default info.

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 tool reads the full content of an Excel file including text and images. It specifies the verb 'Read', resource 'Excel file', and scope 'full content', distinguishing it from siblings as the primary comprehensive analysis tool.

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 usage context, indicating it is ideal for comprehensive analysis of documents with text and images (e.g., requirement definitions, reports). However, it does not explicitly state when not to use it or mention alternatives like read_excel_data for text-only needs.

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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