Recommendations
get_api_v1_profile_recommendationsGet profile Given and Received recommendations By URN Group: Profile. Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| urn | No |
get_api_v1_profile_recommendationsGet profile Given and Received recommendations By URN Group: Profile. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| urn | No |
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?
No annotations are present, and the description does not disclose any behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. The simplicity of the function is implied by the word 'Get', but no explicit behavioral information is provided, leaving the burden on the description unfulfilled.
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 very brief and to the point, lacking unnecessary fluff. However, it includes extraneous metadata like 'Billing per call: 1 Credits' which does not aid understanding of the function. The structure is a single sentence, which is concise but could be more informative without becoming verbose.
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?
The description does not explain what the response will contain, how to interpret the recommendations, or any context about the profile. With no output schema provided, the description entirely fails to give users a complete picture of what to expect, making it inadequate for effective usage.
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 only parameter 'urn' has no description in the schema or the main description. The description mentions 'By URN' but does not explain what a URN is or how to format it. This is a severe lack of semantic meaning for the parameter, and the description does not compensate for the low schema coverage.
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 clearly states the tool retrieves both given and received recommendations for a profile, using the verb 'Get' and specifying the resource (profile). It distinguishes from other profile tools by focusing on recommendations, which no sibling tool covers.
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 provides no explicit guidance on when to use this tool versus alternatives. It only states what it does, without mentioning conditions or exclusions. Since sibling tools cover distinct endpoints, the context is implicit but not clearly articulated.
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 target distinct resources (profiles, posts, companies, jobs), but there is notable overlap among profile-related endpoints (about, overview, details, full) and company insights vs. employees_data vs. insights. An agent could struggle to pick the right one without reading fine-grained descriptions.
The naming follows a consistent snake_case pattern starting with 'get_api_v1_', making it predictable. However, there are typos ('siilar', 'campany'), mixed terms (lookup vs. search vs. get), and extremely long redundant prefixes that reduce clarity, though the overall style is uniform.
With 50 tools, this is well above the 25-tool threshold, making the surface feel heavy and overwhelming. While the domain is broad (LinkedIn data), many endpoints could be consolidated (e.g., profile about/overview/details/full) to reduce the count without losing functionality.
For a read-only LinkedIn data API, the coverage is quite comprehensive: profiles, posts, companies, jobs, searches, geos, skills, and services are all represented. Obvious gaps are minimal—only a few advanced search filters or batch operations could be missing, but core data retrieval is well covered.