Certifications
get_api_v1_profile_certificationsGet Lists professional certifications by URN Group: Profile. Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| urn | No |
get_api_v1_profile_certificationsGet Lists professional certifications 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?
Annotations are absent, so the description carries the full burden of behavioral disclosure. It only adds billing cost and the URN group scope; it does not clarify read-only behavior, authentication needs, pagination, error conditions, or response shape. While not contradictory, the disclosure is minimal for a tool with no annotation support.
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 short and the billing sentence adds useful cost information. The main sentence is grammatically odd ('Get Lists professional certifications') but not bloated; it is concise at the cost of polish.
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?
For a one-parameter retrieval tool with no output schema and no annotations, the description under-delivers: it does not state the return format, any limits, or whether the URN is optional given that no parameters are required. The billing note helps, but the description leaves too much unspecified for confident 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?
Schema description coverage is 0%, and the single 'urn' parameter is undocumented in the schema. The description's phrase 'by URN Group: Profile' adds some meaning by indicating that the URN identifies a profile, but it does not explain requiredness, format, or what happens if no matching profile exists.
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 identifies the action as listing professional certifications and scopes them to the Profile URN group, which distinguishes it from sibling profile tools like profile_education or profile_skills. The phrasing 'Get Lists professional certifications' is grammatically awkward but clear enough that the tool returns certifications for a profile.
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?
There is no explicit guidance on when to use this tool instead of sibling profile tools, no exclusions, and no mention of alternatives. The phrase 'by URN Group: Profile' weakly implies it is for a specific profile's certifications, but the description does not help an agent choose between this and similar profile endpoints.
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.