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Flux LinkedIn MCP

LinkedIn Post Search

linkedin_post_search

Search LinkedIn posts by keyword. Costs 5 credits per call. Returns a single page of matching posts.

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query / keywords
filtersNoOptional filters
refreshNoBypass the cache and re-run the search live (costs 5 credits). Default false: a previously-fetched result is returned free, with how long ago it was retrieved.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It usefully states 'Costs 5 credits per call' and 'Returns a single page of matching posts,' which adds real behavioral context beyond the schema. However, it omits pagination mechanics, rate limits, authorization needs, and what a 'single page' contains, leaving material gaps for an unannotated search tool.

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?

Three short sentences, front-loaded with the core action and followed by cost and result-shape notes. Every sentence earns its place and there is no filler.

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

Completeness3/5

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

There is no output schema and no annotations, so the description should carry more of the return-value and operational context. It says results are a 'single page' but does not explain page size, how to retrieve subsequent pages, or what fields matching posts include. Given the nested filters and paginated search behavior, this is adequate but incomplete.

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%, so the query, filters, and refresh parameters are already well documented in the schema, including the cache-bypass behavior of refresh. The description adds no parameter-level detail beyond implying keyword input, so the baseline 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 gives a specific verb and resource: 'Search LinkedIn posts by keyword.' An agent can immediately tell this is a keyword search over LinkedIn posts. However, it does not distinguish the tool from several close siblings such as search_posts, find_similar_posts, linkedin_company_posts, and linkedin_profile_posts.

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 states a credit cost but gives no guidance on when to use this tool versus search_posts, find_similar_posts, or any of the other post-related siblings. There are no exclusions, prerequisites, or alternative-routing hints beyond the bare keyword-search framing.

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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