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nongtiensonpro

Document RAG MCP

get_document

Retrieves all indexed chunks and provenance for a given document ID, enabling AI agents to access full document content and source citations from the RAG system.

Instructions

Return all indexed chunks and provenance for one document id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It indicates a read operation via 'Return' but does not discuss error behavior, authentication requirements, or the potentially large payload implied by 'all indexed chunks'. This is adequate for a simple read but not richly transparent.

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 a single, front-loaded sentence with no wasted words. It states the action, the resource, and the scope in order of importance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return value details are covered elsewhere. However, the description does not mention how document_id should be obtained, what happens when the id is invalid or not yet indexed, or whether the response is large. For a one-parameter read it is nearly complete but leaves small, relevant gaps.

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?

With 0% schema description coverage, the description must add parameter meaning. It does clarify that document_id selects the document whose chunks and provenance are returned, but it does not specify the expected id format or how to obtain a valid id. This is minimal but useful context beyond the schema's type and title.

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 verb and resource: 'Return all indexed chunks and provenance for one document id.' It specifies a single document id, which distinguishes this get-by-id tool from siblings like list_documents and search_documents without requiring the schema.

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 the use case: call this when you have a specific document id and need its chunks/provenance. It does not mention alternatives or when not to use it, so usage guidance is only implied, not explicit.

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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