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Flux LinkedIn MCP

List Audience Segments

list_segments

List all audience segments for the authenticated user, with member counts. Audience segments are named groups of people (e.g. 'ICP — VPs of Marketing', 'Champions'). Free — costs 0 credits.

Input Schema

NameRequiredDescriptionDefault
typeNoOptional filter by segment type ('manual', 'smart', or 'auto_stream')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden, and it does disclose two useful traits: results include member counts and the call is free (0 credits). It omits pagination behavior, result limits, and whether empty results or permissions errors are possible, so the disclosure is partial.

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?

Three short sentences, front-loaded with the action and resource. The gloss defining audience segments is arguably extra but cheap and helps the agent confirm the resource; the cost note is placed last where it belongs.

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?

For a one-optional-param, read-only list tool with no output schema, the description covers purpose, scope, expected return content, and cost. The main remaining gap is not distinguishing this tool from the other segment-related tools.

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% and the single optional enum parameter (type: manual/smart/auto_stream) is fully documented in the schema. The description never mentions filtering by type, so it adds nothing beyond the schema; baseline 3 applies.

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?

States a specific verb and resource ("List all audience segments") plus scope ("for the authenticated user") and return content ("with member counts"). It doesn't explicitly differentiate from near-siblings like list_segment_templates or resolve_segment, but the core purpose is unambiguous.

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?

No guidance on when to use this versus list_segment_templates, resolve_segment, or list_collections, and no prerequisites stated beyond "authenticated user." Usage is only implied by the verb.

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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