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panther-labs

Panther MCP Server

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list_log_sources

Read-only

Retrieve and filter log sources from Panther's security monitoring platform to identify available data streams for analysis and investigation.

Instructions

List log sources from Panther with optional filters.

Permissions:{'all_of': ['View Rules']}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoOptional cursor for pagination from a previous query
log_typesNoOptional list of log types to filter by
is_healthyNoOptional boolean to filter by health status (default: True)
integration_typeNoOptional integration type to filter by

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The annotations already declare readOnlyHint=true, indicating this is a safe read operation. The description adds the permissions requirement ('View Rules'), which provides useful context beyond annotations. However, it doesn't describe behavioral aspects like pagination behavior (implied by cursor parameter but not explained), rate limits, or what constitutes a 'log source' in Panther's context.

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 efficiently structured in two sentences: one stating the core purpose and scope, another providing critical permission information. There's no wasted text, though the permission format could be more natural. It's appropriately sized for a list operation with filters.

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

Completeness4/5

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

Given the tool has annotations (readOnlyHint), 100% schema coverage, and an output schema (implied by context signals), the description provides adequate context. It covers the core purpose, mentions filtering capability, and includes permission requirements. For a read-only list tool with good structured documentation, this is reasonably complete.

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?

With 100% schema description coverage, all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond mentioning 'optional filters' generically. This meets the baseline of 3 since the schema carries the full burden of parameter documentation.

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 clearly states the verb ('List') and resource ('log sources from Panther'), making the purpose immediately understandable. It distinguishes itself from siblings like 'list_alerts' or 'list_detections' by specifying the resource type. However, it doesn't explicitly differentiate from potential similar tools like 'get_log_type_schema_details' beyond the resource name.

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

Usage Guidelines3/5

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

The description mentions 'optional filters' which implies usage when filtering is needed, but provides no explicit guidance on when to use this tool versus alternatives. There's no mention of prerequisites like the required permissions (though those are listed separately), nor comparison to sibling tools like 'get_http_log_source' for specific log source types.

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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