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FoundZiGu

ragflow-mcp-server-fixed

by FoundZiGu

Retrieve chunks

retrieve

Retrieve relevant text chunks from a RAGFlow dataset using a dataset ID and query question.

Instructions

Retrieve relevant chunks directly from a RAGFlow dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesDataset id
questionYesRetrieval query
page_sizeNoMax chunks, default 8
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'retrieve relevant chunks directly,' implying a read-only operation, but does not mention what happens on invalid dataset_id, whether it modifies data, or any error handling.

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?

The description is a single concise sentence with no wasted words. However, it could be slightly expanded to improve clarity without sacrificing conciseness.

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

Completeness2/5

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

Given the lack of output schema and annotations, the description is too minimal. It does not explain the return format, what 'chunks' are, or any pagination details, leaving the agent underinformed for a retrieval tool.

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 coverage is 100%, so the input schema already describes each parameter. The description adds no additional meaning beyond what is in the schema, meeting the baseline for high 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 verb 'retrieve' and the resource 'chunks directly from a RAGFlow dataset'. It distinguishes from sibling tools like 'ask_configured_chat' and 'chat', which involve conversational interactions.

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 chunks, but it does not provide guidance on when to use this tool over siblings (e.g., when to use 'ask_configured_chat' instead). No explicit when-not or alternatives are mentioned.

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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