get_posts_postId_commentsReturns an empty list when the post has no comments. Group: Posts. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of results per page. | |
| start | No | Offset of the first result. Pass the `cursor` value from the previous response to fetch the next page. | |
| postId | Yes | The post's `ugcPostId`, taken from `/person-profile/posts` or `/company/posts`. Use `ugcPostId` here, not `activityId`. |
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?
With no annotations provided, the description carries the behavioral transparency burden. It usefully discloses the empty-list edge case, which adds real value beyond the schema. However, it does not mention pagination behavior, error cases, authentication needs, or the general response shape, leaving meaningful behavioral gaps.
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 brief and front-loads the most useful behavioral fact: the empty-list return. The 'Group: Posts' and 'Billing per call' sentences are not very useful for tool selection, but they are short and do not substantially harm readability.
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?
There is no output schema, so the description should explain what the response contains and how pagination works, but it only mentions the empty-list case. The schema hints at pagination via 'start' and 'cursor', but the description leaves the actual response structure and when to use pagination unspecified.
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?
Schema description coverage is 100%, so the schema already documents postId, count, and start in detail. The description adds no additional parameter meaning, which fits the baseline of 3 when the schema carries the parameter documentation burden.
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 title 'List comments on a post' plus the description's statement that it 'Returns an empty list when the post has no comments' make the tool's core function clear. However, the description itself never directly states that it returns comments, relying on the title, and it does not distinguish this from the sibling get_posts_postId_reactions.
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?
No guidance is given about when to use this tool versus alternatives such as get_posts_postId_reactions or get_company_posts. The description only provides a conditional behavior, group, and billing information, none of which helps an agent decide between this tool and its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.