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Flux LinkedIn MCP

Get Outreach Queue

get_outreach_queue

Return a prioritized outreach queue. Provide exactly one of three scopes: • campaign_id — full Constellation queue with composite_score, pool, recommended_action, and prior outreach_log entries (the original campaign-scoped behavior). • segment_id — people in a saved audience segment, ranked by their engagement count against your tracked profiles' posts. No composite_score. • linkedin_urls — an ad-hoc list of LinkedIn URLs, same engagement-count ranking as segments. Free — costs 0 credits.

Input Schema

NameRequiredDescriptionDefault
poolNoOptional filter: only return entries in this pool. Only meaningful for `campaign_id` scope; ignored for segment / urls.
limitNoMax entries to return (1-200, default 50)
segment_idNoAudience segment id (engagement-count scoring)
campaign_idNoCampaign id (full Constellation scoring)
linkedin_urlsNoAd-hoc LinkedIn URL list (engagement-count scoring); max 200

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description must carry the behavioral load and it does well: it discloses per-scope return content (composite_score, pool, recommended_action, prior outreach_log entries), states that segment/url modes omit composite_score, and declares the operation is free (0 credits). It stops short of describing auth requirements or what happens on zero/multiple scope input.

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?

One lead sentence plus three tight bullets, with the mutual-exclusivity constraint front-loaded and the cost note last. Every clause adds information; nothing restates the name or title.

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?

With no output schema and no annotations, the description fills the gap by explaining what each scope returns and how ranking differs, which is what an agent needs to choose and call correctly. Response envelope shape, pagination/truncation behavior, and error semantics when scope selection is invalid remain undocumented.

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?

Schema coverage is 100%, so 3 would be the baseline; the description adds real meaning by explaining that segment_id and linkedin_urls rank by engagement count against tracked profiles' posts while campaign_id uses full Constellation scoring, which the schema does not convey. The mutual-exclusivity rule across the three id parameters is also only in the description.

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?

States a specific verb and resource ('Return a prioritized outreach queue') and immediately disambiguates three distinct scopes, each with its own ranking model and output fields. An agent can tell which mode fits its data without opening the schema.

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 'Provide *exactly one* of three scopes' constraint is explicit, and each bullet explains what that scope means and what it returns, which effectively encodes when to use it. It does not name sibling tools (e.g. get_outreach_path, list_segments) that an agent might also consider, so it falls short of a full when/when-not/alternatives statement.

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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