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linkdapi-the-best-linkedin-professional-data-api

Get Full Profile

get_api_v1_profile_full

Get full profile data in 1 request (everything included) Group: Profile. Billing per call: 1 Credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urnNo
usernameNo

TDQS

B3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full transparency burden. It discloses that the response includes 'everything', which hints at a large payload, but fails to mention important behaviors such as the need to provide either urn or username (both optional in schema), auth requirements, or potential rate limits. The billing note is cost-related, not behavioral, and adds little transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (one sentence plus metadata) and front-loaded with the core purpose. It avoids bloat, though the 'Group: Profile' and 'Billing per call' fragments are tangential. Overall, it is efficient and does not waste words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 2 optional parameters and no output schema, the description is inadequate. It does not explain how the system selects a profile when both params are optional, what the response structure looks like, or how this 'full' response differs from other profile endpoints beyond being comprehensive. The lack of any usage or parameter guidance makes the tool poorly specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it does not explain the parameters at all. The schema only shows optional urn and username with examples, but the description never clarifies that these are alternative identifiers or that at least one is required. The description adds no meaningful semantic value beyond the schema's bare field names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves full profile data in a single request, using 'everything included' to indicate comprehensive coverage. This distinguishes it from the many granular profile sibling tools (e.g., get_api_v1_profile_about, get_api_v1_profile_skills) that provide only specific sections.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied but not explicit. The phrase '1 request' suggests using this as a one-stop alternative to multiple calls, but the description does not explicitly say when to choose this over granular endpoints or mention any prerequisites. It is not misleading, but lacks clear 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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TDQS

C2.7/5.0
Disambiguation3/5

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.

Naming Consistency3/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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