Skip to main content
Glama

ncloud_get_log_count_total

Read-only

Retrieve the total collected log count from Cloud Log Analytics to monitor log volume and assess data ingestion.

Instructions

Get the total collected log count in Cloud Log Analytics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionCodeNoRegion code (default kr)
Behavior2/5

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

The readOnlyHint annotation already declares this is a safe read operation. The description adds no additional behavioral information such as whether the count is for a specific time range, whether it resets, or what constitutes 'collected'. Since it adds no context beyond the annotation, it falls below the baseline.

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 filler or repetition. It perfectly balances brevity with the necessary information for a simple tool.

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?

For a simple count tool with no output schema, the description is minimally adequate. However, given the closely related sibling tools (ncloud_get_log_count_recent, ncloud_get_log_count_by_period, ncloud_get_log_count_by_type), it lacks the contextual differentiation needed to avoid confusion about which count is being retrieved.

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?

The input schema has 100% description coverage for the single optional parameter (regionCode), so the schema already explains its meaning. The description adds no parameter information, but the baseline of 3 applies because the schema does the heavy lifting.

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

Purpose4/5

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

The description uses a specific verb 'Get' and identifies the resource as 'total collected log count in Cloud Log Analytics', which is clear and distinguishes it from siblings like ncloud_get_log_count_recent or ncloud_get_log_count_by_period. However, it doesn't explicitly state how this 'total' differs from those other counts, so it's not a 5.

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 gives no guidance on when to use this tool versus alternatives. For example, it doesn't mention that this is a global aggregate while the sibling tools filter by time or type. The agent is left to infer from the name alone.

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/sjk4425/ncloud-gov-mcp-server'

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