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get_document

Retrieve full text content from documents by ID or path, extracting text from PDF, DOCX, and PPTX files for AI agent access to knowledge bases.

Instructions

Retrieve the full text content of a document by ID or path. For text files the original content is returned; for binary formats (PDF, DOCX, PPTX) the extracted text is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
containerIdYesContainer ID or name
fileIdYesDocument ID (UUID) or virtual path (e.g., '/docs/readme.md')
Behavior3/5

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

Annotations already declare destructiveHint=false, indicating a safe read operation. The description adds useful context beyond this: it explains that text files return original content while binary formats return extracted text, and clarifies the input types (ID or path). However, it does not disclose other behavioral traits like error handling, rate limits, or authentication needs, which would be valuable given the lack of output schema.

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 two sentences with zero waste: the first sentence states the core purpose and parameters, and the second clarifies behavior for different file formats. It is front-loaded with essential information and appropriately sized for the tool's complexity.

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 moderate complexity (2 required parameters, no output schema), the description is mostly complete. It covers the purpose, input semantics, and behavioral nuances for file formats. However, it lacks details on output structure (e.g., text format, error responses) and any usage constraints, which would help the agent invoke it correctly without an output schema.

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

Parameters3/5

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

Schema description coverage is 100%, with clear descriptions for both parameters (containerId and fileId). The description adds marginal value by reinforcing that fileId can be a 'UUID or virtual path', but does not provide additional syntax, format details, or examples beyond what the schema already documents. This meets the baseline for high schema coverage.

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 specific action ('Retrieve the full text content') and resource ('document by ID or path'), distinguishing it from siblings like list_files (which lists metadata) or search_knowledge (which searches content). It specifies the exact output (text content) and how it handles different file formats, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving document content, but does not explicitly state when to use this tool versus alternatives like list_files (for metadata) or search_knowledge (for searching within documents). No exclusions or prerequisites are mentioned, leaving the agent to infer context from the tool name and description alone.

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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