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ryanmat

io.github.ryanmat/logicmonitor

by ryanmat

get_datasources

Read-onlyIdempotent

Retrieve datasources from LogicMonitor with optional filters for name, appliesTo expression, and pagination to find specific monitoring data sources.

Instructions

List datasources from LogicMonitor

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results
filterNoRaw filter expression (overrides other filters). Example: name~CPU,group:Core
offsetNoPagination offset
name_filterNoFilter by name (substring)
applies_to_filterNoFilter by appliesTo expression

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

C2.9/5.0
Behavior2/5

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

The description adds no behavioral context beyond what annotations already declare (read-only, idempotent, non-destructive). It does not mention pagination, filtering semantics, return shape, or any operational behavior such as rate limits or auth needs. Since annotations cover the safety profile but the description contributes no extra behavioral disclosure, it falls to 2.

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, front-loaded sentence with no extraneous wording. However, it is extremely terse and essentially restates the tool name, offering no structural advantage beyond being short. It earns a 4 for lack of waste, but is not exemplary because it doesn't structure additional helpful content.

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?

With no output schema and a relatively simple but parameterized list operation, the description should explain return values, pagination behavior, or how the filters interact. It provides none of that, leaving the agent to infer behavior from the parameter names and the tool name. For a 5-parameter tool with no output schema, this is a notable gap, so a score of 2 is warranted.

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 description coverage is 100%, with each parameter (limit, filter, offset, name_filter, applies_to_filter) having its own description including an example for filter. The tool description itself adds no parameter-specific meaning, but the baseline is 3 given the rich schema. The description neither clarifies nor obscures parameters, so 3 is appropriate.

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 states a clear action ('List') and resource ('datasources from LogicMonitor'), making the primary purpose unambiguous. However, it does not explicitly distinguish this from sibling tools like get_datasource (singular) or get_device_datasources, relying on the plural form and name to suggest a list operation. This is clear but lacks explicit sibling differentiation, hence 4.

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 over alternatives such as get_datasource or get_device_datasources. It does not mention any context, prerequisites, or filter scenarios. With zero usage guidance, the agent must infer from the name and schema, so a score of 2 is appropriate.

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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