get_company_postsReturns the same post structure as /person-profile/posts.
This endpoint is addressed by slug only. Group: Companies. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The company's short name, as it appears in its LinkedIn URL. | |
| count | No | Number of posts per page. | |
| start | No | Offset of the first result. Pass the `cursor` value from the previous response to fetch the next page. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are not provided, so the description carries the burden of disclosing behavioral traits. It does mention billing per call (1 Credit) and that it returns the same post structure as another endpoint, which is useful, but it does not disclose mutation/safety properties, rate limits, auth needs, or what happens with missing/invalid slugs. The `slug`-only constraint is helpful but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loads the key behavioral fact (same post structure as another known endpoint), then explains addressing and group/billing. It is efficient and avoids unnecessary padding, though the billing detail is marginal for tool invocation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the schema covers all parameters and provides pagination hints, the description is mostly adequate for a filtered read-style endpoint. However, without annotations, the description does not state whether this operation is read-only or whether any authorization is required, and it does not explain the `cursor` pagination flow, which is partly in the schema. The sibling tools suggest a broader API context, but the description alone is not fully complete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all three parameters (`slug`, `count`, `start`), including defaults and a pagination hint for `start`. The description adds context that `slug` is the company's short name as in its LinkedIn URL, which is already in the schema. Since schema_description_coverage is high (100%), the description does not need to add much, and it complements the schema by clarifying the endpoint's addressing mode.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description says it returns the same post structure as `/person-profile/posts`, and is addressed by `slug` only, which clearly identifies the resource and the key identifier. However, it does not explicitly distinguish itself from sibling tools like `get_person_profile_posts` or `get_posts_postId_comments` beyond the `slug` addressing and group label.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this endpoint for a company's posts, addressed by `slug`. It does not explicitly state when to use this tool over siblings, nor does it mention when not to use it. The reference to pagination via `cursor` in the parameter schema provides some context, but the description itself offers no alternative routing guidance.
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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Most tools map to distinct resource-action pairs, but `get_company_companyId_employees` and `get_people_search` can both return person listings, creating minor overlap. `get_company_posts` vs `get_person_profile_posts` is clear by resource name, so confusion is limited.
All tools follow a `get_<resource>` pattern with path-like segments, but there are minor inconsistencies such as `get_people_search` (plural) vs `get_person_profile` (singular), and redundant segments like `get_company_companyId_employees`. Overall the pattern is recognizable and predictable.
Twelve tools is well-scoped for a read-only LinkedIn data access server. The surface covers companies, jobs, people, and posts without unnecessary duplication or excessive fragmentation.
The core read workflows for company, job, person, and post data are well covered. A notable minor gap is the lack of a standalone `get_post` tool to fetch a post's details by ID, though post content appears in company and person post listings.