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ihiteshgupta

linkedin-mcp-server

by ihiteshgupta

linkedin_create_post

Create a text post on LinkedIn with customizable visibility: public, connections only, or members only.

Instructions

Create a text post on LinkedIn. Supports different visibility options: PUBLIC (everyone), CONNECTIONS (1st degree connections only), or LOGGED_IN (LinkedIn members only).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe content of the post (max 3000 characters)
visibilityNoPost visibility: PUBLIC (default), CONNECTIONS, or LOGGED_IN
Behavior2/5

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

No annotations are present, so the description must carry the full burden. It discloses visibility options but does not mention authentication needs, rate limits, or what happens if the character limit is exceeded. For a creation tool, it lacks important behavioral context.

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?

Two sentences, front-loaded with the purpose. No unnecessary words. Efficient and clear.

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?

Given the tool's simplicity (2 parameters, no output schema), the description is adequate but incomplete. It explains purpose and visibility, but lacks guidance on when to use vs. creating article posts and does not describe any return value or side effects.

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 baseline is 3. The description adds detail for the visibility parameter by explaining enum meanings (e.g., '1st degree connections only' for CONNECTIONS), but adds nothing for the text parameter beyond the schema. Overall, marginal added value.

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 clearly states 'Create a text post on LinkedIn' with a specific verb and resource. It distinguishes from sibling tools like 'linkedin_create_article_post' which handles article posts.

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 implies usage for text posts but does not explicitly state when to use this tool versus alternatives (e.g., linkedin_create_article_post). No when-not-to-use guidance is provided.

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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