Skip to main content
Glama

rag_add_chunking

Add document chunking strategies to your RAG pipeline by specifying a project directory, enabling better retrieval and processing of large documents.

Instructions

Add document chunking strategies

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
directoryYesProject directory
Behavior2/5

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

With no annotations, the description carries full behavioral disclosure burden, but it only implies a mutating/additive operation. It does not state whether files or configs are modified, whether an existing project is required, or what side effects to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no redundancy, but it is under-specified rather than efficiently informative. It adds little value beyond the tool name and does not earn its place by providing actionable detail.

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?

This is a minimal description for a tool with no annotations, no output schema, one undocumented parameter, and no usage guidance. An agent would not know how to invoke it correctly or what outcome to expect, making it incomplete for practical use.

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

Parameters2/5

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

Schema coverage is 50%; only 'directory' has a description, while 'api_key' is completely undocumented. The description mentions none of the parameters and does not clarify what api_key is for or how directory is used for chunking strategies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('Add') and a resource ('document chunking strategies'), so it is not a pure tautology. However, it does not explain what 'adding' entails, what target it applies to, or how it differs from sibling RAG tools like rag_generate_pipeline and rag_optimize_retrieval.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool, what prerequisites are required (e.g., an existing RAG project), or when to prefer it over sibling tools that also relate to RAG pipelines. The usage context is entirely implied by the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/barnburner121/claude-plugin-marketplace'

If you have feedback or need assistance with the MCP directory API, please join our Discord server