Skip to main content
Glama

HDFS DFSAdmin Report

hdfs_dfadmin_report

Generate a DFSAdmin-style report on HDFS cluster capacity and DataNode status using Ambari metrics.

Instructions

Produce a DFSAdmin-style capacity and DataNode report using Ambari metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_nameNo
lookback_minutesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must convey behavioral traits. While 'report' implies a read operation, there is no explicit mention that it is non-destructive, no disclosure of authentication needs, rate limits, or potential side effects. The description's brevity leaves significant behavioral ambiguity.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it lacks structure. While it is not verbose, it does not efficiently front-load key details; it is under-specified rather than concisely informative.

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 complexity of a tool that produces a report from Ambari metrics, the description is too minimal. It does not explain what the report contains beyond 'capacity and DataNode', does not describe parameter effects, and omits any usage context or prerequisites. The existence of an output schema partially compensates, but overall the description is incomplete.

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

Parameters1/5

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

The schema has 0% description coverage, and the description does not mention any of the two parameters (cluster_name, lookback_minutes). It fails to add any meaning or context beyond the parameter names and types, leaving the agent unable to understand how to use them.

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 tool produces a DFSAdmin-style capacity and DataNode report using Ambari metrics. The verb 'produce' and specific resource 'DFSAdmin-style capacity and DataNode report' differentiate it from sibling tools which deal with configurations, requests, alerts, and services.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, contexts, or exclusions for usage, leaving the agent without criteria to decide if this tool is appropriate.

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/call518/MCP-Ambari-API'

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