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GenOffice extract text

genoffice_extract_text

Extract readable text from Office documents and PDFs (docx, xlsx, pptx, pdf). Returns content as markdown-style text with slide and table structure, so you can review a document before editing it.

Instructions

Extract readable text from an Office or PDF file using GenOffice engines (docx/xlsx/pptx/pdf). Returns the document content as markdown-ish text with slide/table structure. Use this to read the content of a document before editing it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to the file (.docx, .xlsx, .pptx, .pdf)
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that output is markdown-ish with slide/table structure, and that it's a read-only extraction. However, it doesn't disclose behavior for unsupported formats, large files, binary content limitations, or what happens with password-protected files. For a read-only tool with no annotations, this is adequate but not rich.

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?

Two sentences covering purpose, input scope, output format, and use case. Zero filler. It's slightly redundant in restating file extensions that already appear in the schema (and in the parameter description), but it's efficiently front-loaded and every sentence earns its place.

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?

Despite no output schema and no annotations, the description conveys format, structure, and intended usage. It informs the agent what to expect (markdown-ish text with slide/table structure). Given a single parameter fully documented and no nested complexity, the description is largely complete; it could mention failure modes (unsupported file types) but that's a minor gap for a straightforward extraction tool.

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 a single 'path' parameter, and the description reinforces it by restating the supported file extensions (.docx, .xlsx, .pptx, .pdf). The description adds the absolute-path requirement contextually and confirms supported types, which complements the schema's extension list. With 100% coverage and one parameter, the value-add is modest but present.

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?

Specific verb (extract) + resource (readable text from Office/PDF files) + explicit format list (docx/xlsx/pptx/pdf). The return type (markdown-ish text with slide/table structure) is clearly stated. This clearly distinguishes it from the numerous sibling genoffice_*_patch/create/delete tools, which are mutation-focused.

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 says 'Use this to read the content of a document before editing it,' which anchors the primary use case and differentiates it from sibling editing tools. It doesn't enumerate 'when not to use' nor mention alternatives by name, but the preceding sentence establishes clear context, and the pre-edit framing is sufficient since the siblings are self-evident mutations.

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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