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rajfirke

sumo-logic-mcp

by rajfirke

list_fields

List all built-in and custom fields to see their names, data types, and states, helping you understand available fields for searching and creating field extraction rules.

Instructions

List all fields (built-in and custom).

Returns field names, data types, and states. Useful for understanding what fields are available for searching and building field extraction rules.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that the tool returns field names, data types, and states, which is important for an agent to know. The read-only nature is implied by 'List', but it does not explicitly state that it has no side effects or mention permissions. Still, the output description adds meaningful value beyond the empty input schema.

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 only two sentences, with the main purpose front-loaded. It avoids redundancy and every sentence contributes useful information: the first defines the action and scope, the second explains the return value and use case. This is appropriately concise.

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

Completeness5/5

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

For a simple list tool with no parameters and an output schema, the description is complete. It states what the tool does, what it returns, and why it is useful. The sibling-tool context and zero-parameter schema mean there are no complex gating conditions or inputs to document. The output schema handles detailed return structure, so the description's summary is sufficient.

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

Parameters4/5

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

The tool has zero parameters, so the schema coverage is trivially 100%. According to the rubric, a zero-parameter tool receives a baseline of 4. There is no need for parameter descriptions; the description correctly focuses on the output and purpose.

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 begins with 'List all fields (built-in and custom)', which clearly identifies the operation (listing), the resource (fields), and the scope (all built-in and custom). This distinguishes it from sibling tools like list_field_extraction_rules, which focus on extraction rules rather than fields themselves.

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

Usage Guidelines4/5

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

The description states 'Useful for understanding what fields are available for searching and building field extraction rules.' This provides a clear context for when to use the tool. It does not explicitly mention alternatives or when not to use it, but the use case is specific enough to guide selection among sibling tools.

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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