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BACH-AI-Tools

LinkedIn Data API MCP Server

get_companys_post

Retrieve the last 50 posts from a company's LinkedIn page using the company username. Supports pagination to access additional results beyond the first page.

Instructions

Get last 50 posts of a company. 1 credit per call

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesExample value: microsoft
startNouse this param to get posts in next results page: 0 for page 1, 50 for page 2, 100 for page 3, etc.
paginationTokenNoIt is required when fetching the next results page. The token from the previous call must be used.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions credit cost but does not disclose pagination behavior beyond parameter hints, nor does it describe what happens on errors or rate limits. Minimal behavioral disclosure.

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, no filler. Information is front-loaded and concise. Every word earns its place.

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?

No output schema exists, yet description does not specify return structure or format. It mentions 'last 50 posts' but not field details. For a simple list retrieval, it is barely adequate but missing important context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and schema descriptions are already clear. The description adds no additional meaning beyond '1 credit per call'. It could have elaborated on username format or pagination behavior but did not.

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 clearly states the action (Get) and resource (last 50 posts of a company). It distinguishes from siblings like 'get_post' and 'get_company_post_comments' by specifying company scope and count. However, the name 'get_companys_post' is slightly ambiguous and could be clearer.

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 tool over alternatives. Sibling tools like 'get_post', 'get_profiles_posts', and 'get_company_post_comments' exist but no conditions or exclusions are 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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