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kaistenberg

MCP Server for LinkedIn

by kaistenberg

Search Posts

search_posts
Read-only

Search LinkedIn posts globally by keyword to find informal hiring announcements and job leads before they appear in formal job listings.

Instructions

Search LinkedIn posts/content globally by keyword (the "Posts" tab).

Use this to catch informal hiring posts ("we're hiring", "Buscamos ...", "estamos contratando", "join our team") that often appear before a formal job listing exists. This is global content search, distinct from get_feed (your own home feed) and get_company_posts (one company's page).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesSearch keywords (e.g., "Buscamos Unity", "AI automation hiring")
max_pagesNoScroll depth as result "pages" of ~5 scrolls each (1-10, default 3). Content search is an infinite scroll, so this caps how far the page is scrolled rather than fetching discrete pages.
date_postedNoOptional recency filter. One of "past-24h", "past-week", "past-month"; the "past_24_hours" / "past_week" / "past_month" spellings used by search_jobs are accepted too. Omit for any time.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful context about global search scope and purpose, but does not disclose behaviors like pagination/scroll depth or rate limits beyond what's in the schema. This is adequate but not exceptional.

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 sentences, front-loaded with the action, then targeted usage guidance. Every sentence earns its place with no fluff or repetition of schema details.

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?

The description covers purpose, usage, and sibling differentiation. An output schema exists, so return value details are handled. It could mention the infinite-scroll behavior or open-world limitations (though the schema parameter notes it), but overall it is quite complete for a search tool.

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 structured fields already explain all three parameters. The description adds example search keywords, but does not add new semantic meaning beyond what the schema provides. Baseline 3 is appropriate.

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 opens with a specific verb+resource+scope: 'Search LinkedIn posts/content globally by keyword'. It explicitly distinguishes from sibling tools get_feed and get_company_posts, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description gives concrete when-to-use guidance: 'Use this to catch informal hiring posts' with example keywords. It also names exclusions by contrasting with get_feed and get_company_posts, telling the agent when not to use this tool.

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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