Skills & Titles lookup
get_api_v1_g_title_skills_lookupsearch for a keyword and get relevent skills and titles with their IDs Group: skills. Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | No |
get_api_v1_g_title_skills_lookupsearch for a keyword and get relevent skills and titles with their IDs Group: skills. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It discloses billing ('1 Credits per call') which is a cost consideration, but it does not mention side effects, authentication, rate limits, or absence of destructive actions. The tool appears read-only from the name, but this is not explicitly stated.
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 concise, consisting of two short sentences that convey the core purpose and billing. Minor issues include a typo ('relevent') and the cryptic 'Group: skills' phrase, but overall it is efficient and front-loaded.
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 low-complexity tool with one parameter and no output schema, the description covers the essential aspects: what it does, what it returns (skills and titles with IDs), and cost. It does not elaborate on result formatting or limitations, but given the simplicity, this is adequate.
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 schema only provides a 'query' string with an example. The description adds meaning by stating it is a 'keyword' used for searching, which clarifies its role. However, it does not specify whether the parameter is required or any constraints (e.g., max length), leaving some ambiguity given 0% schema description 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 searches for a keyword and returns relevant skills and titles with their IDs. It uses a specific verb ('search') and specifies the resource ('skills and titles'). It distinguishes from siblings like services lookup by mentioning 'skills' explicitly, though the parenthetical 'Group: skills' is ambiguous.
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 the tool is for looking up skills and titles based on a keyword, but it does not explicitly state when to use this over alternative lookup tools (e.g., services lookup). No when-not or alternative tools are mentioned, so usage guidance is minimal.
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.